Alcohol Dehydrogenases

4.06 Alcohol Dehydrogenases H J Edenberg and W F Bosron, Indiana University School of Medicine, Indianapolis, IN, USA ª 2010 Elsevier Ltd. All rights reserved.

4.06.1 4.06.2 4.06.3 4.06.4 4.06.4.1 4.06.4.2 4.06.5 4.06.6 4.06.7 4.06.8 4.06.9 4.06.9.1 4.06.9.2 4.06.9.3 4.06.9.4 4.06.10 References

Introduction Nomenclature Gene Organization and Relationships Regulation of Gene Expression Distribution in Different Tissues Regulation of ADH Gene Expression Major Polymorphisms Catalytic Mechanism Protein Structures Substrate Selectivity Roles in Toxicity and Clinical Significance Ethanol Metabolism, Pharmacokinetics, and Toxicology Metabolism and Toxicology of Other Alcohols and Aldehydes ADH Polymorphisms and Risk for Alcoholism ADH Polymorphisms and Other Diseases Future Directions and Needs in Field

Abbreviations ADH ALDH BLAST

alcohol dehydrogenase aldehyde dehydrogenase basic local alignment and search tool

4.06.1 Introduction The mammalian alcohol dehydrogenases (ADHs) are a family of enzymes that catalyze the oxidation and reduction of a wide variety of alcohols and aldehydes. They are abundant in the liver but are present to different extents in other tissues. The individual members of this family have different but overlapping substrate specificities, and probably play a general detoxifying role. They have attracted considerable interest due to their key role in the metabolism of ethanol (beverage alcohol), which modulates the effects of ingested ethanol on the body. Individual differences in ADH isozymes and expression affect risk for alcoholism, tissue damage, and developmental abnormalities including fetal alcohol spectrum disorders. In this chapter, we focus primarily on the human ADHs and their role

EST NCBI ORF SNP

111 111 113 114 114 115 118 119 120 121 122 122 123 124 125 126 126

expressed sequence tag National Center for Biotechnology Information open reading frame single nucleotide polymorphism

in the metabolism of endogenous and dietary alcohols, including ethanol.

4.06.2 Nomenclature There are multiple forms of ADH (note that ADH in roman type is used herein for ADH enzymes, whereas ADH in italic is used to represent the genes encoding ADHs; Table 1). The isozymes consist of homo- and heterodimers with subunits of approximately Mr 40 000 (Bosron et al. 1993). Studies of electrophoretic and kinetic properties, antigenicity, and amino acid sequence originally led to their assignment into three classes (Vallee and Bazzone 1983). Two additional classes have since been identified in humans, and an apparent sixth class in rodents (Hoog and Brandt 1995; Zheng 111

112 Alcohol Dehydrogenases Table 1 Human alcohol dehydrogenase genes and proteins Approved gene symbola

Approved gene namea

ADH1A

Alcohol dehydrogenase 1A (class I), alpha polypeptide Alcohol dehydrogenase 1B (class I), beta polypeptide Alcohol dehydrogenase 1C (class I), gamma polypeptide Alcohol dehydrogenase 4 (class II), pi polypeptide Alcohol dehydrogenase 5 (class III), chi polypeptide Alcohol dehydrogenase 6 (class V) Alcohol dehydrogenase 7 (class IV), mu or sigma polypeptide

ADH1B ADH1C

ADH4 ADH5 ADH6 ADH7

Synonymsb

Class

RNA: RefSeq accession ID

Subunit encodedc

Protein: RefSeq accession ID

ADH1

I

NM_000667

NP_000658

ADH2

I

NM_000668

ADH3

I

NM_000669

 ADH1A  ADH1B  ADH1C

ADH-2 ADH2 ADH-3 ADH3 ADH-5 ADH5 ADH-4 ADH4

II

NM_000670

NP_000661

III

NM_000671

V

NM_000672

IV

NM_000673

 ADH4  ADH5 NDd ADH6 ,  ADH7

NP_000659 NP_000660

NP_000662 NP_000663 NP_000664

a

HUGO Gene Nomenclature Committee. Note that the synonyms based on class designations (Duester et al. 1999) create much confusion in the literature, because one must determine what is meant by, for example, ‘ADH4’: class II (officially ADH4) or class IV (officially ADH7). We use the approved symbols here. c Protein subunits have traditionally been named with Greek symbols, but can also be named based upon the gene encoding them. d RNA detected; protein not detected. b

et al. 1993). Class I isozymes (ADH1A, ADH1B, and ADH1C) generally have a low Km for ethanol and play the major role in ethanol metabolism (Table 2). Class II isozymes (ADH4) contribute to ethanol oxidation at higher ethanol concentrations. Class

III isozymes (ADH5) are relatively inactive with ethanol, except at high concentrations, and play important roles in metabolism of formaldehyde and nitric oxide. The class IV isozyme (ADH7) that is present in stomach and esophagus has a high Km

Table 2 Catalytic activity of ADH isozymes with ethanol

Variant ADH1Aa ADH1B1a (Arg47/Arg369) ADH1B2b (His47/Arg369) ADH1B3b (Arg47/Cys369) ADH1C1b (Arg271/Ile349) ADH1C2b (Gln271/Val349) ADH4b ADH5a ADH7a

Protein subunit

Km, ethanol (mM)

Activity Vmax (min1)

Activity at 22 mM ethanol

Structure PDB ID (reference)

 (alpha) 1 (beta1) 2 (beta2) 3 (beta3) 1 (gamma1) 2 (gamma2)  (pi)  (chi) ,  (sigma, mu)

4

30

25

0.013

5.2

5.2

1.8

190

176

61

140

37

1hso (Niederhut et al. 2001) Ihsz (Niederhut et al. 2001) 1hdy (Hurley et al. 1994) 1htb (Davis et al. 1996)

0.1

32

32

0.14

20

20

11

9

6

>1000

100

<2

30

1800

760

PDBID - Protein Data Bank ID; www.rcsb.org/pdf/home. a Kinetic data determined at pH 7.5, 2.4 mM NAD (Hurley et al. 2002). b Kinetic data at pH 7.5 with 0.5 mM NAD (Lee et al. 2004). Activity at 22 mM ethanol (S) was calculated from v ¼ (Vmax?S)/(KmþS).

1hto (Niederhut et al. 2001) 1e3e (Svensson et al. 2000) 1mao (Sanghani et al. 2002b) 1d1s (Xie et al. 1997)

Alcohol Dehydrogenases

and a high Vmax for ethanol oxidation (Table 2). ADH6 was discovered as a gene (Yasunami et al. 1991) and has not yet been found as a protein in human tissue.

4.06.3 Gene Organization and Relationships The seven human ADH genes lie in a head-to-tail array along chromosome 4, an arrangement that has been largely conserved among mammals (Figure 1). They have clearly evolved from a single ancestral gene, deduced by Jornvall and colleagues to be a class III form (Jornvall et al. 1995, 2003; Nordling et al. 2002). The conservation of both sequences and intron positions, as well as the retention of the head-to-tail organization (Figure 1), indicates that evolution was by repeated unequal recombinations. The ADH genes have nine exons and eight introns (Figure 2) (Brown et al. 1996; Edenberg and Brown 1992; von Bahr Lindstrom et al. 1991; Yasunami et al. 1991; Yokoyama et al. 1994b; Zgombic-Knight et al. 1995b). ADH6 was originally reported to lack the last exon, but later data suggest that exon 9 is present (Stromberg and Hoog 2000). The introns are in the same positions in all of the genes, with two interesting exceptions: cases of apparent intron movement in the rat Adh1 gene (Crabb et al. 1989) (rat and mouse genes are written Adh; rodents have only a single class I gene, Adh1). In the rat Adh1, the 39 boundary of intron 4 is shifted upstream by 3 nt, resulting in the addition of one amino acid to the protein, and both boundaries of intron 3 have moved upstream by 1 nt, leaving the intron within the same codon (Crabb et al. 1989). Genome annotations relating to rodent Adh6 are not ADH7

113

consistent in different databases; rodents have an Adh6a and Adh6b in the same relative position as the human ADH6 (between Adh1 and Adh4; Figure 1) (Szalai et al. 2002a); however, the rodent genes form a different class of ADH, with only 56–65% amino acid identities to human ADH6. There are processed pseudogenes derived from ADH5 (Hur 1993; Hur and Edenberg 1991, 1992; Matsuo and Yokoyama 1990); the expression of ADH5 but not other ADH genes in germinal cells (Dafeldecker and Vallee 1986) presumably allowed the ADH5 pseudogenes to arise by retrotransposition. Interclass pairwise comparisons of amino acid sequences show about 60–70% identity, while comparisons of enzymes from different species within a class generally show over 80% identity (Brown et al. 1996; Edenberg and Brown 1992; Jornvall et al. 1995). The three human class I ADHs diverged before the split between Old World monkeys and apes; all three have orthologs in chimp and rhesus macaque. The three class I proteins in these primates are 92–94% identical (and 96–98% similar) in amino acid sequence. The close resemblance of these genes appears to be through purifying selection (Oota et al. 2007). Human class I ADHs are 80–88% identical (88–95% similar) to other mammalian class I enzymes (horse, dog, cow, rat, and mouse). Class III enzymes are the most highly conserved. Basic local alignment and search tool (BLAST) analyses showed 99% amino acid identity and 100% similarity among the three primates (human, chimp, and macaque), 95% identity (97–99% similarity) of dog, horse, cow, and rabbit to human, and 93% identity (98% similarity) of mouse. This very high degree of conservation suggests ADH5 plays important metabolic roles.

ADH1C ADH1B ADH1A

ADH6

ADH1C ADH1B ADH1A

ADH6

ADH4

ADH5

Human ADH7

ADH4

ADH5

Chimp Adh7

Adh1

Adh6a

Adh6b

Adh4

Adh5

Adh4

Adh5

Mouse Adh7

Adh1

Adh6a

Adh6b

Rat Figure 1 Arrangement of ADH genes along the chromosome. The arrangement of ADH genes along human chromosome 4, chimp (Pan troglodytes) chromosome 4, mouse (Mus musculus) chromosome 3, and rat (Rattus norvegicus) chromosome 2, based upon NCBI map viewer and BLAST comparisons. Note that rodent Adh6 genes form a different class than the primate ADH6 genes; the annotations are not consistent in different databases; these genes are discussed in Szalai et al. 2002a under the nonstandard names Adh5a and Adh5b.

114 Alcohol Dehydrogenases

1

2 3

45

6

7 8

9

5′

3′ R48H

R370C

Figure 2 Intron/exon structure of ADH1B. The introns and exons of human ADH1B are shown approximately to scale; exons are numbered. Red indicates nontranslated regions. The sites of the two most-studied coding mutations, ADH1BHis48 (ADH1B2) and ADH1BCys370 (ADH1B3) are indicated by triangles below the exons (numbering according to dbSNP). This gene structure is found in all ADH genes, although there are differences in intron lengths.

4.06.4 Regulation of Gene Expression 4.06.4.1

Distribution in Different Tissues

The human ADHs have diverged not only in substrate specificity (see Section ‘Substrate Selectivity’) but also in their patterns of expression. There are major differences between the classes and among the class I ADHs. Class III genes are expressed in all tissues of all species examined (Duley et al. 1985; Engeland and Maret 1993; Giri et al. 1989b; Pares et al. 1984), but at different levels (Giri et al. 1989b; Holmes 1978; Hur et al. 1992). The other classes all show restricted expression, in overlapping but distinct patterns. Human liver contains ADH proteins of class I (ADH1A, ADH1B, ADH1C, -, -, and -ADH) (Adinolfi and Hopkinson 1979; Smith 1986; Smith et al. 1971, 1972), class II (ADH4, -ADH) (Adinolfi and Hopkinson 1979; Duley et al. 1985; Li and Bosron 1987; Li et al. 1977), and class III (ADH5, -ADH) (Adinolfi and Hopkinson 1979; Adinolfi et al. 1984; Giri et al. 1989a, 1989b). Class IV

(ADH7, - or -ADH) is absent from liver (Moreno and Pares 1991; Yokoyama et al. 1994a, 1995; ZgombicKnight et al. 1995b). Class V (ADH6) mRNA is present (Figure 3), but the protein has not been reported (Yasunami et al. 1991; Zgombic-Knight et al. 1995a). Each of the ADH genes has a different pattern of expression outside the liver (Bosron et al. 1993; Edenberg 1991; Edenberg and Brown 1992; ZgombicKnight et al. 1995a). ADH7 (- or -ADH) is a major stomach isozyme and is present at high levels in esophagus and upper GI tissues (Moreno et al. 1994; Stone et al. 1993b; Yin et al. 1990, 1993). Class I ADHs are not detected in brain (Beisswenger et al. 1985) nor was their mRNA even when RNA was concentrated several 100fold (Giri et al. 1989b); recent studies of expressed sequence tags (ESTs; see below) confirm the lack of class I ADH mRNA in brain. It is interesting that ADH1B is expressed in human blood vessels but not in rat vessels (Allali-Hassani et al. 1997); this is confirmed by EST data. Thus for studies of the effects of alcohol on vascular tissues, rats are not a good model organism. The primary form of ADH expressed in fetal liver is ADH1A (Ikuta and Yoshida 1986; Smith et al. 1972). ADH1B is detected at low levels by mid-gestation, increasing to becomethepredominant ADH by late gestation (Pikkarainen and Raiha 1969; Smith et al. 1971). ADH1C is first detected about 6 months after birth (Pikkarainen and Raiha 1967, 1969; Smith et al. 1971). Once turned on, these genes remain active throughout adult life. Total ADH activity with ethanol as substrate (primarily reflecting class I enzymes, with contribution from class II) increases about 12-fold from early fetuses

1600 1400 1200 ADH1A 1000

ADH1B ADH1C

800

ADH4 600

ADH5 ADH6

400

ADH7

200 – Liver

Intestine

Stomach

Esophagus

Lung

Trachea

Figure 3 Expression of ADH mRNAs in different human tissues. Relative expression of ADH mRNAs, as transcripts per million, based on EST data in UniGene.

Alcohol Dehydrogenases

to about 5 years (Pikkarainen and Raiha 1967, 1969; Smith et al. 1971). Class I ADH mRNA also increases about 10-fold from fetus to adult (Ikuta and Yoshida 1986). Studies of gene expression in humans are difficult. Most samples are from autopsy at variable times postmortem or from biopsy or surgical specimens from individuals in which the tissue is abnormal. Analysis of mRNA is usually more sensitive than analysis of proteins, although RNA is less stable and more subject to degradation. Expression of the mRNA is essential for expression of the protein, and often (but not always) correlates with the amount of protein; protein levels may also be regulated posttranslationally. With the accumulating data from the genome project, it is now possible to survey relative mRNA levels in different tissues in silico. For example, one can use the data and expression profile tool in National Center for Biotechnology Information (NCBI) UniGene, which tallies ESTs (random shotgun sequencing from cDNA libraries, representing transcripts) from different tissues. The tissues have been sequenced to different extents (ranging from 13 000 to over 1.1 million transcripts), so the lower limit of detection varies. Analyses of ESTs in March 2008 reinforce some of the above protein data and throw new light on tissues not often examined (Figure 3). As expected, all tissues express at least some ADH5 mRNA, although the amount varies 10-fold. ADH5 was the only ADH detected in the brain, the tissue sequenced in most depth; even 1 part per million of other ADH mRNAs could have been detected, but none were. Among the tissues examined, liver expresses the most ADHs, all except ADH7, and does so at moderately high levels (Figure 3). ADH1B and ADH4 mRNAs are the most abundant forms in liver. Intestine expresses ADH1B, ADH1C, and ADH5 at moderate levels. Surprisingly, mRNA for the class I ADHs was not detected in human kidney, although ADH1B was expressed at high levels in the adrenal gland. ADH1B is widely expressed (30/45 tissues); only the ubiquitous ADH5 is expressed in more tissues. The highest concentration of ADH-related transcripts are of ADH1B in adipose tissue (sequenced at lowest coverage, so the lack of detection of other ADHs represents <76 transcripts/million); ADH1B is also very abundant in trachea and liver, and vascular tissue. ADH1A is not expressed in many tissues (only detectable in 4/45). ADH1C is expressed at highest levels in intestine and at moderate levels in liver, pharynx, and stomach (Figure 3); it was detected in 15/45 tissues. ADH4 has a restricted expression pattern; it is expressed at high levels in liver and at moderate levels in mammary

115

tissue, but at only trace levels in three other tissues. ADH7 is most abundant in the upper gastrointestinal tract, particularly esophagus, mouth, and pharynx; it is also present at high levels in trachea, but not present in liver, intestine, and kidney (Figure 3). ADH6 mRNA is found at high levels only in liver and at modest levels in kidney, with traces in several other tissues, but the protein has not been purified from human tissue. 4.06.4.2 Regulation of ADH Gene Expression The mammalian ADH promoters have multiple cis-acting elements, both positive and negative, in their proximal regions (Figure 4) (reviewed in more detail in Edenberg 2000). This provides flexibility for regulation in different tissues. Among these elements are TATA boxes typical of genes expressed in tissuespecific patterns, which are present in most of the ADH genes. The class III ADH genes (e.g., human ADH5 and mouse Adh5), which are G þ C-rich and have characteristics of housekeeping genes, lack TATA boxes. The promoters of the human class I genes, ADH1A, ADH1B, and ADH1C, are very similar out to about 750 bp (Edenberg and Brown 1992; Edenberg et al. 1994; Stewart et al. 1990a). The similarity of ADH1A and ADH1B continues out to about 2.3 kb, but ADH1C diverges due to the insertion of a repetitive element related to the long terminal repeat of ERV9, an endogenous retrovirus; this retrovirus is also present in the baboon ADH1C (Edenberg et al. 1994). Proximal promoters of the ADH genes and the transcription factors that bind to them are reviewed in detail by Edenberg (2000); some aspects will be highlighted here. The transcription initiation site is the same for all three human (and baboon) ADH genes and lies within a 14-bp conserved region. The 59 nontranslated regions are also very similar. The region extending to about 55 bp upstream of the transcription initiation site contains a TATA box flanked by two sites to which C/EBP family members can bind (Figure 4) and activate expression; there is a second TATA box about 10 bp upstream from the transcription start site (Brown et al. 1994; Stewart et al. 1990a, 1990b, 1991; van Ooij et al. 1992). In the region between bp 60 and 95 are two very important positive cis-elements: an E-box (CACGTG) that can bind the upstream stimulatory factor and a G3T site that binds Sp1 (Brown et al. 1992, 1994, 1996; Carr and Edenberg 1990; Carr et al. 1989; Potter et al. 1991; Stewart et al. 1990a, 1991). Just upstream from the G3T site in ADH1B there is a

116 Alcohol Dehydrogenases

ADH1A

HNF1

ADH1B

HNF1

ADH1C

HNF1

ADH4

G

G

Sp1 USF

Sp1

CTF

4 C/EBP

5

F2

3

F

F1

C/EBP

Sp1

CTF

6

ADH5

ADH6

CTF

USF

9

C/EBP

C/EBP C/EBP

2 C/EBP

E

1

CSp1

D

D

E

C/EBP

C

B Sp1

A

B

A

C/EBP

ADH7

D C/EBP

C

B C/EBP

A

Figure 4 Proximal promoters of the human ADH genes. Schematic of transcription factor binding sites in the proximal approximately 300 bp of the seven human ADH genes. Arrow denotes transcription start site. Data from Brown et al. 1992, 1994, 1996; Edenberg et al. 1993; Hur and Edenberg 1992; Kotagiri and Edenberg 1998; Li and Edenberg 1998; Zhi et al. 2000.

CTF/NFI-related site that acts as a negative element (Brown et al. 1994; Edenberg et al. 1993). Although the ADH1A and ADH1C sequences are very similar in that region, the comparable site is not occupied; rather, a different CTF/NFI-related site is located slightly further upstream (Brown et al. 1994, 1996; Edenberg et al. 1993). The proximal promoters of class I genes show some cell-type specificity in vitro, although not to the extent of tissues. They are expressed in HeLa cells as well as in some but not all hepatoma cells. ADH1A and ADH1B promoters function well in H4IIE-C3 rat hepatoma cells (Brown et al. 1992, 1994, 1996; Edenberg 2000; Edenberg et al. 1993) that express endogenous class I ADH (Wolfla et al. 1988). Endogenous class I ADHs are not detectable in the human hepatoma cell line HepG2 (<105 of the level in liver (Tian and Edenberg 2005)), and transfected promoters work poorly in those cells and in Hep3B (Stewart et al. 1990a, 1990b). Cell specificity in these promoter assays can be altered dramatically by coexpression of a single transcription factor. Coexpression of C/EBP stimulates expression of ADH1B in H4IIE-C3 and HepG2 cells about two- to fourfold (Brown et al. 1994, 1996; Stewart et al. 1990b; van Ooij et al. 1992). C/EBP stimulates expression of both ADH1A and ADH1B in HeLa cells about 10-fold and in CV-1 cells (which barely express these promoters without it) about 20-fold (Brown et al. 1994, 1996).

ADH1A expression is similarly stimulated by C/EBP in H4IIE-C3 cells (Brown et al. 1996) but was reported to be nonresponsive in HepG2 cells (van Ooij et al. 1992). Other C/EBP family members also stimulate expression in HepG2 and H4IIE-C3 cells (Brown et al. 1996; van Ooij et al. 1992). Cotransfection with HNF-1 stimulates the ADH1A promoter but not the others (van Ooij et al. 1992) even though HNF-1 has been shown to bind to ADH1B (Brown et al. 1994). ADH1B contains a weak glucocorticoid-responsive element (Dong et al. 1988; Winter et al. 1990). ADH1C contains a retinoic acid-responsive element and can be transactivated by retinoic acid when the retinoic acid receptor  or  is cotransfected into Hep3B and HepG2 cells; it is inhibited by cotransfection with the retinoic acid receptor  or the thyroid hormone receptor (Duester et al. 1991; Harding and Duester 1992). More recently, the effects of more distant elements have been examined. In ADH1A, a negative element has been identified between bp 1873 and 1558, relative to the translational start site, and a positive element identified from bp 2459 to 2173 (Dannenberg et al. 2005). Both of these had stronger effects in hepatoma cells than in kidney fibroblasts. The positive element was bound by the transcription factor GATA-2. There was a cis-element between 5.4 and 5.7 kb that stimulated transcription more in hepatoma cells than in fibroblasts and bound

Alcohol Dehydrogenases

HNF-3 in fibroblasts but not in hepatoma cells (Dannenberg et al. 2005). A larger region, extending out to 6.4 kb, had even greater differential effects on the two cell types, stimulating transcription twofold in hepatoma cells and decreasing it 14% in fibroblasts (Dannenberg et al. 2005). There are negative elements between 0.6 and 1.1 kb and between 2.6 and 4 kb upstream of the transcription initiation site of ADH1C; the more distal site showed cell specificity, decreasing activity more in HeLa cells than in hepatoma cells (Chen et al. 2002, 2005). A cell-specific cis-element between 1.05 and 1.5 kb upstream was particularly interesting: it increased transcription sixfold in hepatoma cells while reducing it more than fourfold in HeLa cells, leading to a nearly 30-fold difference in effect. This cell-specific cis-element is part of a U3 repeat of a human endogenous retrovirus that inserted into the ADH1C gene after the duplications that created the three class I ADH genes. Regulation through this site appears to result from the combination of both the ubiquitous transcription factor NF-Y and a hepatoma/liver-specific factor that both can bind to a subsequence of the repetitive element (Chen et al. 2002). The fact that this repetitive element has strong regulatory effects highlights the need to consider such elements in genomic analyses, yet repetitive sequences are not represented in standard tiling arrays used for many chromatin immunoprecipitation studies. Different haplotypes of the ADH1C promoter affect its expression. Three of the regulatory regions of ADH1C noted above were sequenced in a set of 16 individuals, and 13 polymorphisms were discovered, including an insertion of 66 bp (a repetitive element), a 5-bp variation, and 12 SNPs (Chen et al. 2005). Different combinations of these variations (natural haplotypes) had different effects on promoter activity. Although the 66-bp insertion alone did not significantly alter promoter activity, in combination with three SNPs there was a twofold effect on activity (Chen et al. 2005). The effects of the haplotypes could not be deduced from linear combinations of the effects of individual sites, suggesting complex interactions. The ADH4 proximal promoter functions in both hepatoma cells (H4IIE-C3) and kidney fibroblasts (CV-1) cells (Li and Edenberg 1998). There are nine cis-acting elements in the proximal promoter (extending 450 bp upstream of the transcription initiation site); proteins in liver extracts bind to seven of these (Figure 4 shows the most proximal six sites) (Li and

117

Edenberg 1998). Transient transfection assays demonstrated that most of these sites increased transcription activity in hepatoma cells; the exceptions were sites 4 and 6 (Li and Edenberg 1998). Site 8 strongly reduced activity (Li and Edenberg 1998). Two sites can be bound by C/EBP family proteins; cotransfection with C/EBP, C/EBP, or C/EBP dramatically stimulated promoter activity (Li and Edenberg 1998). Site 4 was particularly interesting; it could bind both C/EBP family proteins and also c-Jun (a component of AP1), suggesting that competition and/or cooperation between transcription factors in those families could regulate expression. In fact, a mutation that abolished C/EBP binding but not c-Jun binding decreased activity in a manner that suggests interaction with proteins bound further upstream (Li and Edenberg 1998). Different haplotypes of the ADH4 promoter have different activities in vitro. Three SNPs in the proximal promoter were tested, and one of them, 136 bp upstream of the translational start site, was shown to affect promoter activity. Haplotypes containing the A allele (on the sense strand) had twofold higher promoter activity than haplotypes containing the C allele (Edenberg et al. 1999). The other two SNPs had no detectable effect. The ADH5 promoter is TATA-less and G þ Crich (Hur and Edenberg 1992), as is typical of promoters for genes expressed in all tissues. The ADH5 promoter shows surprising complexity for a gene expressed ubiquitously (Figure 4); the multiplicity of cis-elements extends at least 1 kb upstream (Hur and Edenberg 1995). The cis-acting elements include sites for Sp1, AP2, AP1, HNF5, and C/EBP family members, as well as heat shock elements, serumresponsive elements, E-boxes, and CCAAT sites (Hur and Edenberg 1995). This complexity regulates the different levels to which ADH5 is expressed in different tissues (Figure 3). Among the cis-acting elements several are cell-specific, acting as a positive element in one cell and a negative or null element in another (Hur and Edenberg 1995). A pair of Sp1 sites that flank the transcription start site (sites C and B; Figure 4) defines a minimal promoter that works very well in all cell lines tested (Hur and Edenberg 1995). These two sites are critical for promoter function, as is the presence of Sp1 (Kwon et al. 1999). Two related proteins, Sp3 and Sp4, can compete for binding at these sites and repress transcription (Kwon et al. 1999). FBI-1, a POX-domain transcription factor, can bind to the site just upstream of these Sp1 sites (site D; Figure 4) and repress transcription by interacting with the zinc fingers of Sp1 and

118 Alcohol Dehydrogenases

interfering with its binding (Lee et al. 2002). ADH5 is also regulated posttranscriptionally; it is unusual in having two ATGs upstream of the ATG that initiate the ADH polypeptide (Hur and Edenberg 1992). These small upstream open reading frames (ORFs) can influence expression: altering the length of the short ORFs by 12 nt (four codons) altered gene expression twofold (Hur and Edenberg 1995). Mutation of either site individually led to twofold increased activity of the promoter in some cell types and less effect in others; the increases were even larger when measured by in vitro translation assays (Kwon et al. 2001). The proximal ADH6 promoter can also direct transcription in both hepatoma (H4IIE-C3) and non-hepatoma (CV-1) cells (Zhi et al. 2000). A mutation that truncated the promoter within the distal part of site C (Figure 4) dramatically reduced transcription. Altering the TATA sequence within site C drastically reduced transcription, but altering 5 bp in the distal part of the site (implicated by the truncation experiment) had only modest effect (Zhi et al. 2000). Although C/EBP family proteins could bind to site C, cotransfection with C/EBP or C/EBP did not stimulate activity (Zhi et al. 2000). A region between 1.6 and 2.3 kb upstream of the transcription start site stimulated transcription in hepatoma cells and inhibited it in fibroblasts; this region had two cisacting elements, one of which was a negative element in fibroblasts but had no detectable effect in hepatoma cells and the other was a positive element in hepatoma cells but had no effect in fibroblasts (Zhi et al. 2000). Thus cell-type specificity results from a combination of inhibition and stimulation. The ADH7 proximal promoter (extending 232 bp upstream of the transcriptional start site; Figure 4) functioned in several cell types including hepatoma cells (Kotagiri and Edenberg 1998), although the gene is not normally expressed in liver. The 600 bp immediately upstream of the proximal promoter had no significant effect on promoter activity. Site A (Figure 4) bound c-Jun, a component of AP1; a mutation that abolished c-Jun binding dramatically reduced promoter activity (Kotagiri and Edenberg 1998). Site B can bind C/EBP, but the fact that it affected activity similarly in cells that express C/ EBP and those that do not suggest other factors play a dominant role. Mutation of site C, which can bind both C/EBP and c-Jun, doubled activity in cells that do not express C/EBP, but did not significantly affect activity in cells that did express C/EBP. Cotransfection with either C/EBP or C/EBP

decreased promoter activity, which might partly explain the lack of ADH7 in adult liver (Kotagiri and Edenberg 1998). In addition to the proximal promoter elements, more distant elements are needed for proper expression of the ADH genes, as shown by studies in transgenic mice. The proximal 2.5 kb sequence upstream of the mouse Adh1 gene allowed expression in kidney and adrenal tissues, but not in liver (Xie et al. 1996); within this region were sequences allowing androgen repression in adrenals but not induction in kidney. A longer construct (containing 10 kb upstream) did respond appropriately to androgens in both kidney and adrenals, but still was not expressed in liver (Xie et al. 1996). Much longer flanking sequences, contained in a bacterial artificial chromosome that extended 110 kb upstream and 104 kb downstream of Adh1, promoted expression at the normal levels in many tissues tested, including liver (Szalai et al. 2002b). The human class I ADH genes also require distant elements for proper expression. A sequence located between ADH1C and ADH7 was important for high levels of expression of ADH1A, ADH1B, and ADH1C in liver and ADH1C in stomach of transgenic mice, and for reducing expression in other tissues (Su et al. 2006). The region was conserved between mouse and human, and contained a binding site for the transcription factor HNF1 that was shown to be essential for expression in liver but not in stomach (Su et al. 2006). Most studies of transcriptional regulation examine a single promoter sequence from one individual. It is increasingly clear that sequence differences between individuals can affect transcriptional regulation, as noted above for ADH1C (Chen et al. 2005) and ADH4 (Edenberg et al. 1999). Clearly, we need to know much more about the expression of all ADH genes in different tissues and during development, as well as in different individuals, to appreciate how the enzymes they encode function in metabolism of ethanol and other substrates, as well as vulnerability to the effects of these substances.

4.06.5 Major Polymorphisms Polymorphisms that affect the amino acid sequence of the class I ADHs have been known for a long time. The classic ones that have been most thoroughly studied alter amino acids 47 (rs1229984) and 369 (rs2066702) in ADH1B and amino acids 271 (rs1693482) and 349 (rs698) in ADH1C (Table 2; note that the amino

Alcohol Dehydrogenases

acid numbering used here is based upon the mature protein lacking the N-terminal Met, for consistency with the protein structure databases and the discussion below; numbers listed in dbSNP are one higher). ADH1B1 (ADH21 in earlier literature) encodes a protein with Arg47 and Arg369; ADH1B2 (ADH22) with His47 and Arg369, and ADH1B3 (ADH23) with Arg47 and Cys369. These three forms have widely different kinetic properties (Table 2). The frequencies with which they are found differ greatly in different populations, as recently reviewed (Edenberg 2007; Ehlers 2007; Ehlers et al. 2007; Li et al. 2007; Moore et al. 2007; Scott and Taylor 2007). ADH1B2 is found at very high frequencies in East Asia, at high frequencies in Western Asia, and at low frequencies in western Europe or Africa (Han et al. 2007; Li et al. 2007). ADH1B3 is found at moderate frequencies in Africa and African Americans but only at very low frequencies elsewhere. Similarly, the distribution of ADH1C1 (Arg271/Ile349; previously ADH31) and ADH1C2 (Gln271/Val349; ADH32) alleles varies greatly in different populations. A different variant of ADH1C, Pro351Thr (rs35719513), has a more limited distribution, with the Thr351 allele found almost only in the Americas (Osier et al. 2002a). There is also a rare stop mutation in ADH1C (G78Ter; rs283413). Detailed information on allele frequencies in many populations, compiled by the Kidd laboratory, can be found at The Allele Frequency Database (Rajeevan et al. 2003). There are coding variations in ADH4 also (Hoog et al. 1987). One of these, Ile308Val (rs1126671), affects the stability of the protein and has modest effects on Km (Stromberg et al. 2002). The effects of coding SNPs in ADH5 and ADH7 have not been studied at the protein level. Polymorphisms that affect the expression of ADH genes have only been studied recently. A single SNP (rs1800759) located 136 bp upstream from the translation start site of ADH4 makes a twofold difference in promoter function in vitro: the A allele expresses at a level twice as high as the C allele (nt on the strand oriented as the RNA) (Edenberg et al. 1999). An SNP 9 bp downstream from the transcriptional start site in ADH5 reduces promoter activity about 30% (Hedberg et al. 2001). A haplotype containing the low-activity allele at that site and two SNPs further upstream reduced ADH5 promoter activity by about 50%; the upstream polymorphisms did not themselves affect promoter activity (Hedberg et al. 2001). Several combinations of SNPs (haplotypes) upstream of ADH1C also affect promoter function (Chen et al. 2005), as noted above.

119

In addition to these SNPs of known function, there are many other SNPs in the ADH region, some of which could affect the expression of the genes but have not yet been studied. The HapMap project has reported 449 variants that are polymorphic in European Americans in the 384-kb region containing the human ADH genes (and 10 kb flanking sequence on each side); this underestimates the actual variation because SNPs of lower allele frequencies or found in other populations are not well represented in that database. The variations are not inherited independently; nearby SNPs are more likely to be inherited together, but the pattern is complex (see, e.g., Edenberg et al. 2006; Han et al. 2005, 2007; Li et al. 2007; Osier et al. 2002b). The nonrandom coinheritance of alleles is called linkage disequilibrium and reflects the genetic history of humans. Strong linkage disequilibrium between the coding variants in ADH1B and ADH1C complicates analyses of their effects on risk for alcoholism (Chen et al. 1999; Osier et al. 1999, 2002b, 2004). There is very strong linkage disequilibrium in the ADH4/ADH5 region (Edenberg et al. 2006) and a major recombination hot spot within ADH7 (Birley et al. 2008; Han et al. 2005). The implications of this complexity have not yet been fully considered in studies of the effects of variants in these genes. Recent studies have revealed that the frequency of ADH1B2 has increased in two distinct regions of Asia, East Asia and the Middle East, in a pattern that suggests the increase in each area was independent (Han et al. 2007; Li et al. 2007). ADH1B2 is under positive selection in some East Asian populations, but the selection appears to have operated primarily on a particular haplotype that includes a SNP 5 kb upstream in a potential regulatory region (Han et al. 2007). The frequency of ADH1B2 differs by ethnic group among East Asian populations, suggesting a cultural aspect to the selective pressure, with indications that selection in some populations may have focused on this regulatory region (Li et al. 2008). Thus regulatory variation appears to have contributed to the selective advantage of the well-known ADH1B2 coding variation. Previous studies that focused exclusively on coding SNPs should be reexamined in light of the many noncoding variations.

4.06.6 Catalytic Mechanism The mammalian NADþ-dependent ADHs obey a sequential kinetic mechanism that proceeds through an enzyme–alcohol–NADþ ternary complex where

120 Alcohol Dehydrogenases

the hydride transfer reaction occurs to form the enzyme–aldehyde–NADH complex (Dunn 1985). Most of the mammalian ADH isozymes obey an ordered kinetic mechanism where NADþ binds to form the binary E–NADþ complex and there is a conformational change in protein structure that facilitates the binding of alcohol to form the ternary complex (Eklund and Branden 1979). Catalysis in the ternary complex involves the transfer of a hydride ion (a proton plus two electrons) from the C-1 of alcohol to C-4 of the NADþ nicotinamide ring. The horse and yeast enzymes exhibit stereospecificity for hydride transfer. The pro-R hydrogen of ethanol is transferred to the re-face of NADþ generating the pro-R form of NADH (Walsh 1979). Recent structural and kinetic studies with the glutathione-dependent formaldehyde dehydrogenase (ADH5) demonstrate a departure from this ordered mechanism; the reaction can proceed by random addition of either substrate (Sanghani et al. 2002a). The equilibrium of the reaction with ethanol as substrate at pH 7 (1  104 at pH 7) favors the reduction of acetaldehyde to ethanol (Walsh 1979). Hence, the concentrations of NADþ relative to NADH and of alcohol relative to aldehyde must be high for the net oxidation of ethanol to occur. Concentrations of these compounds in rat liver 2 h after administration of 2 g kg1 ethanol are about 30 mM for ethanol, 40 mM for acetaldehyde, 0.5 mM for NADþ, and 1 mM for NADH (Lumeng et al. 1980). Hence, the highly efficient mechanisms for oxidation of acetaldehyde to acetate (via aldehyde dehydrogenase) and the reoxidation of NADH to NADþ in mitochondria allow the net oxidation of ethanol to occur in vivo. All members of the family of human ADHs are zinc metalloenzymes. The active site zinc is buried within a cylindrical apolar substrate channel (Hurley et al. 1994). During catalysis, alcohol displaces water and coordinates to the active site zinc as the alcoholate anion. A conserved amino acid proton relay system facilitates transfer of the alcohol proton to water (Eklund et al. 1982). Zinc acts as an electrophilic center to facilitate hydride ion transfer from the alcohol group to NADþ. Removal of the catalytic zinc or substitution with another metal ion substantially decreases catalytic activity (Sytkowski and Vallee 1976). Hence, the main catalytic features of ADH involve selective binding of substrates, metalassisted activation of the substrate, and coordinated hydride ion and proton transfers.

4.06.7 Protein Structures Three-dimensional structures for five different human ADH1 isozymes, a mouse homolog of ADH4 and the human ADH5 and ADH7 isozymes, have been solved by X-ray crystallography (references in Table 2). All of these ADHs have the following general structure: each subunit consists of a coenzyme and a catalytic domain; enzymes are dimers with the dimer interface along the coenzyme-binding domain; there is a cleft between the domains where substrates bind; the catalytic zinc atom is coordinated to 2 Cys and 1 His; and the ‘structural’ zinc atom is coordinated to 4 Cys (Niederhut et al. 2001; Sanghani et al. 2002b; Svensson et al. 2000). The catalytic domain, residues 1–175 and 319–374 in horse ADH, is predominantly composed of -sheet elements and no regular tertiary structure (Eklund et al. 1976). The coenzyme domain, residues 176–318 in horse ADH, has six parallel -sheet structures flanked by helices in a regular pattern characteristic of a Rossman dinucleotide-binding fold (Buehner et al. 1973). A key feature of the ordered kinetic mechanism of horse ADH was revealed by the conformational change in apoenzyme that is induced by coenzyme binding (Eklund and Branden 1979). This involves a rotation of the catalytic domain toward the central coenzyme-binding domain to narrow the cleft between the domains and ‘form’ the alcohol-binding site. Similar coenzyme-induced conformational changes are seen for the human ADH1 isozymes (Hurley et al. 1994; Niederhut et al. 2001). However, structures for ADH4 (Svensson et al. 2000) and ADH5 (Sanghani et al. 2002b) reveal ‘semi-open’ conformations that create a larger alcohol substrate-binding site than ADH1. This difference in the conformational change accounts, in part, for differences in substrate specificities. The alcohol-binding pocket in horse ADH1 and human class I ADHs has been described as a cylinder with a diameter of 7–10 A˚ that extends about 15 A˚ from the protein surface to the catalytic zinc (Niederhut et al. 2001). While the overall amino acid sequence identity among the human class I ADHs is 93%, the identity in the substrate-binding pocket is only 60%. This difference in key residues that line the alcohol-binding site determines the differences in alcohol catalytic efficiency (Tables 2 and 3). For example, the Ala for Phe93 substitution in ADH1A versus ADH1B or ADH1C facilitates

Alcohol Dehydrogenases

efficient oxidation of secondary alcohols (Niederhut et al. 2001; Stone et al. 1989). The alcohol-binding pocket of mouse Adh4 is much larger than horse or human ADH1, which accounts for the observation that the mouse Adh4 cannot be saturated with ethanol but is uniquely active with p-benzoquinone and 9-cis-retinol as substrates (Svensson et al. 2000). Human ADH5 also has low catalytic efficiency for ethanol oxidation, since activity is not saturated at 2 M ethanol. However, the large ADH5 active site is uniquely adapted to accommodate the nitroso and hydroxymethyl glutathione adducts. Arg115 specifically forms a strong ion pair interaction with the Gly carboxylate of glutathione (Sanghani et al. 2002a). The isoprenoid chain in all-trans-retinol fits well in the long alcohol-binding channel of ADH7 that is lined with hydrophobic Leu, Met, and Phe residues (Xie et al. 1997). At the internal end of the alcoholbinding site is the catalytic zinc that acts as a Lewis acid catalyst to coordinate the alcoholate anion and facilitate hydride transfer (Dunn 1985; Walsh 1979). In the original horse ADH1 mechanism, the active site zinc is coordinated to one His and two Cys residues. In apoenzyme, the fourth ligand is water that is exchanged for the alcoholate anion in a ternary ADH–NADþ–alcohol complex (Eklund et al. 1982). Recent studies with ADH5 (glutathione-dependent formaldehyde dehydrogenase) demonstrate a second type of active site zinc coordination where the zinc atom is displaced 2.3 A˚ toward the active site Glu67 so that zinc is coordinated by four amino acid ligands from the enzyme (Sanghani et al. 2002a). The displacement of zinc toward Glu67 may promote ligand (water or alcohol) exchange during catalysis, a hypothesis first proposed by Ryde based upon theoretical computations (Ryde 1995).

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4.06.8 Substrate Selectivity As shown in Table 2, the various isozymes of human ADH differ widely in Kmm for ethanol and Vmax for ethanol oxidation. The Km values for NADþ also vary substantially from about 7–700 mM (Bosron et al. 1993). It is particularly noteworthy that single amino acid substitutions at positions 47 and 369 of the ADH1B isozymes cause very large differences in kinetic constants. The substitution of Arg47 in ADH1B1 by His in ADH1B2, or Arg369 in ADH1B1 by Cys in ADH1B3 results in large differences in Vmax for ethanol oxidation, Km for NADþ, and Km for ethanol (Table 2; Hurley et al. 1990). The differences in kinetic constants are due to changes in hydrogen bonding and electrostatic interactions between side chains of the substituted amino acids and the pyrophosphate group of NAD(H). For example, the substitution of a His47 or Cys369 for Arg at these positions simultaneously decreases affinity for coenzymes and increases the dissociation of coenzyme from the E–NADH complex during ethanol oxidation. These substitutions have a great effect on catalytic rate because the rate-limiting step for ethanol oxidation is dissociation of NADH from the binary complex (Stone et al. 1993a). ADH1C1 has 1.5-fold higher Vmax for ethanol oxidation than ADH1C2 (Table 2). This increase may be related to the substitution of Arg271 in ADH1C1 by Gln, which interacts with the adenine ring of NAD(H) (Niederhut et al. 2001). These in vitro kinetic studies led to the classification of high- versus low-activity SNPs in ADH1B and ADH1C (ADH1B2 vs ADH1B1 and ADH1C1 vs ADH1C2). All of the ADH isozymes exhibit broad substrate specificity for oxidation of primary alcohols. ADH1 and ADH7 isozymes have highest catalytic efficiency for ethanol oxidation (Table 3). For the human ADH

Table 3 Catalytic efficiency of human ADH isozymes for various alcohols

Substrate

ADH1A 

ADH1B1 1 1

ADH1C1  1 1

ADH4 

ADH5 

ADH7 

Ethanol Butanol Pentanol Octanol 12-OH-dodecanoate All-trans-retinol

6.7 1600 nd nd nd 92

29 150 250 1900 330 20

130 2200 2300 16 000 2400 19

4 nd 5300 71 000 1040 650

NS <0.15 11 180 2800 NA

65 2600 3400 nd 3700 1900

ADH variants are identified by the gene and homodimeric protein subunit. The catalytic efficiencies (Vmax/Km in mM1 min1) for all-trans-retinol with all isozymes were determined at pH 7.4 (Yang et al. 1994). For other substrates, kinetic constants for ADH1B1, ADH1C1, ADH4, and ADH5 were determined at pH 10 (Eklund et al. 1990), and at pH 7.4 for ADH7 (Kedishvili et al. 1995) and ADH1A (Stone et al. 1989). NA means not active; NS means not saturated; nd means not determined.

122 Alcohol Dehydrogenases

isozymes, catalytic efficiency (Vmax/Km for alcohol) increases substantially as the chain length of the primary alcohol increases from two carbons in ethanol to six carbons in 1-hexanol. There is a relationship between log of catalytic efficiency versus log of the water:octanol partition coefficient that increases with primary alcohol chain length (Hansch et al. 1972). The approximately linear relationship for ADH1 isozymes indicates that the hydrophobic interaction in the alcohol-binding site is a very important determinant of catalytic efficiency. As shown in Table 3, the isozymes have different preferences for retinol with ADH7 and ADH4 displaying highest catalytic efficiencies. ADH4 displays a unique activity for benzoquinone reduction (Maskos and Winston 1994). ADH5 is also named a glutathione-dependent formaldehyde dehydrogenase because it participates in the important oxidation of s-hydroxymethyl glutathione to formylglutathione in the detoxification pathway for formaldehyde (Koivusalo et al. 1989). More recently, ADH5 was shown to reduce s-nitrosoglutathione with NADH to glutathione sulfinamide with the highest catalytic efficiency of any of its substrates (Hedberg et al. 2003). This is an important reaction in controlling the extent of protein s-nitrosylation in cells (Liu et al. 2001). Hence, inhibition of ADH5 is a therapeutic target for regulation of nitric oxide signaling in cells. A catalytic activity for ADH6 has not been identified.

4.06.9 Roles in Toxicity and Clinical Significance 4.06.9.1 Ethanol Metabolism, Pharmacokinetics, and Toxicology Beverage ethanol is absorbed primarily in the small intestine and distributed in total body water. Elimination of ethanol occurs primarily through oxidative metabolism in the liver. There are three basic enzyme systems that contribute to the oxidative metabolism in liver: (1) the family of medium chain, NADþ-dependent ADHs that are the subject of this review, (2) the cytochrome P450 microsomal ethanol oxidizing system represented mainly by CYP2E1 but also CYP1A2 and CYP3A4, and (3) the peroxisomal, H2O2-dependent catalase enzyme (Zakhari 2006). Catalase is considered a minor pathway because its activity is limited by the availability of hydrogen peroxide. The contribution of CYP2E1 to alcohol metabolism can become substantial when animals or humans are exposed to ethanol or other compounds

that induce CYP2E1 in microsomes. Induction of CYP2E1 has significant consequences for the cellular toxicity of ethanol metabolism because of the formation of reactive oxygen species, superoxide anion, and hydroxyl radicals (Lieber 2004). Nonoxidative metabolism of ethanol to form fatty acid ethyl esters contributes minimally to total ethanol metabolism, although fatty acid ethyl esters have been implicated in alcohol-induced tissue damage (Best and Laposata 2003). ADHs are generally acknowledged to be the major pathway for ethanol oxidation in liver (Zakhari 2006). The product of ethanol oxidation is acetaldehyde, which is further oxidized by the NADþdependent mitochondrial and cytosolic aldehyde dehydrogenases (ALDHs) to acetate, which is then metabolized to CO2 and H2O in heart, skeletal muscle, and brain (Zakhari 2006). The step catalyzed by ADH is considered rate-limiting because the capacity for acetaldehyde oxidation by ALDHs exceeds that for ethanol oxidation by ADHs. The rate-limiting factors for ethanol oxidation have been studied in the rat (Crow and Hardman 1989). There are three factors that limit this step: (1) content of ADH in tissues, (2) product inhibition by NADH, determined by the rate of reoxidation of NADH to NADþ in mitochondria, and (3) product inhibition by acetaldehyde, determined by its rate of oxidation to acetate. ADH content and enzyme kinetic studies in rats indicate that ADH operates at about 70% of capacity (Crabb et al. 1983). Nutritional or hormonal manipulations that lower ADH activity in liver (e.g., stress, fasting, and growth hormone) also decrease the rate of ethanol metabolism. Administration of inhibitors of the malate-aspartate shuttle decreases alcohol metabolic rate, whereas administration of fructose increases alcohol metabolic rate (Crow and Hardman 1989). Both of these manipulations affect the cytosolic NADþ/NADH ratio, so this is the factor that can best be manipulated to alter alcohol metabolic rate. It is unlikely that acetaldehyde product inhibition significantly affects alcohol metabolic rate in most individuals. However in Japanese and Chinese who are deficient in the active mitochondrial ALDH2 isozyme, blood acetaldehyde can increase to 50 mM (Adachi et al. 1989) and potentially inhibit ADH-mediated ethanol oxidation. In humans, pharmacokinetic models have been designed to fit ethanol and acetaldehyde elimination rates. Ramchandani et al. (1999) showed that targeted breath ethanol levels could be reached and accurately maintained using an intravenous

Alcohol Dehydrogenases

ethanol infusion adjusted on the basis of a pharmacokinetic model. The original model did not take into account variations in the ADH genes. An accurate alcohol elimination rate can be calculated from the infusion rate in such studies and has been used to demonstrate that individuals with the ADH1B2 polymorphism have a higher ethanol elimination rate (Neumark et al. 2004). Umulis et al. (2005) reported that their pharmacokinetic model could be used to fit/predict acetaldehyde concentration profiles of individuals with differing ALDH2 genotypes. The question of how individual ADH SNPs affect ethanol or acetaldehyde pharmacokinetics in different tissues cannot be addressed without accurate estimates of the amount of various ADH proteins in those tissues. Immunochemical quantification of ADH isozyme expression is complicated by antigenic cross-reactivities among isozymes. Recent mass spectrometry methods for quantifying ADH expression in human tissues may help solve this problem (Janecki et al. 2007). The oxidation of millimolar concentrations of ethanol in liver by ADH and ALDH results in the generation of substantial levels of NADH that can cause hypoxia in hepatocytes located close to the hepatic vein (Zakhari 2006). In rats, the liver NADþ/NADH ratio drops from about 800 to 300 1 h after an ethanol dose of 2 g kg1 body weight (Lumeng et al. 1980). This is largely due to the increase in free NADH concentration to about 1.6 mM, while the free NADþ remains constant at about 0.5 mM. The heightened respiratory chain activity and increased O2 use result from the accumulation of NADH during ethanol oxidation. Another consequence of increased NADH concentration is an increased formation of toxic reactive oxygen species that can react with cellular proteins, lipids, and DNA (Wu and Cederbaum 2003). The formation of the reactive acetaldehyde intermediate by ethanol oxidation is a major toxic factor in ethanol-dependent tissue damage and disease. The concentration of acetaldehyde during ethanol oxidation is normally in the low micromolar range because highly efficient ALDH isozymes oxidize it to acetate. Acetaldehyde’s toxicity derives from its ability to form adducts with proteins and DNA (Zakhari 2006). Acetaldehyde forms lysine amino group adducts with a wide variety of proteins including hemoglobin, albumin, tubulin, lipoproteins, collagen, and enzymes; these adducts can alter protein function (Tuma and Casey 2003). Moreover, protein-acetaldehyde adducts elicit a distinct immune response

123

that may contribute to tissue injury. Acetaldehyde adducts have also been reported with amino groups of DNA and these could account for the genotoxic effects of acetaldehyde (Brooks and Theruvathu 2005). Acetaldehyde adducts are directly implicated in mechanisms of alcohol-related tissue injury. 4.06.9.2 Metabolism and Toxicology of Other Alcohols and Aldehydes The various ADH isozymes exhibit broad, overlapping substrate specificity for primary alcohols (Table 3). The amino acid substitutions in the active sites of different ADHs are consistent with differences in substrate selectivity among the isozymes (Table 2). While considerable effort has been devoted to identify true ‘physiological’ substrates for ADH isozymes, each form undoubtedly plays a general and overlapping role in alcohol metabolism, especially in liver. For ethanol metabolism, the relative contribution of different ADHs to ethanol oxidation with 22 mM ethanol varies about 100-fold. A 70-kg man homozygous for ADH1B2 and ADH1C1 was estimated to have nearly 8 times the ethanol-oxidizing capacity of one homozygous for ADH1B1 and ADH1C1, assuming equal expression levels of the different alleles (Lee et al. 2006). Differences in expression of ‘high activity’ forms of ADH like ADH1B2 or ADH1C1 should have a much greater effect on the pharmacokinetics of ethanol elimination than ‘low activity’ forms like ADH1B1 or ADH4. Ethanol consumption may substantially alter the metabolism of drugs and other dietary alcohols (Lieber 2004). Acute ethanol exposure can inhibit drug metabolism by direct competition with the oxidation of drug or dietary alcohols by ADH and ALDH. Among the many potential ‘physiological’ substrates for ADH, the following alcohols/aldehydes have received most attention: retinol/retinal (vitamin A metabolism), hydroxymethylglutathione (formaldehyde metabolism), s-nitrosoglutathione (NO metabolism), 4-hydroxynonenal (lipid peroxidation intermediates), !-hydroxy fatty acids (fatty acid, leukotriene, and prostaglandin metabolism), 3-hydroxy5-steroids, and 4-hydroxy-3-methoxyphenyl ethanol (dopamine metabolism) (Hoog et al. 2001). There is ADH isozyme selectivity for these substrates. For example, ADH4 is most effective in the reduction of 4-hydroxyalkenals with 5–15 carbon atoms (Sellin et al. 1991). ADH5 is particularly effective in the oxidation of !-hydroxy fatty acids relative to short

124 Alcohol Dehydrogenases

chain alcohols (Table 3). ADH1C, but not ADH1A or ADH1B, catalyzes the oxidation of 3-hydroxy-5steroids that include androstan, estradiol, and digitoxigenin derivatives (McEvily et al. 1988). In many cases, the product of xenobiotic alcohol oxidation creates a toxic intermediate. For example, ethylene glycol (itself not lethal) is oxidized in liver by ADH and ALDH to the highly toxic oxalic acid. Based on the substrate specificity of ADH, Wacker et al. (1965) suggested that ethanol administration could be used in acute care of patients ingesting lethal amounts of ethylene glycol antifreeze. The ethanol-treated patients were able to excrete ethylene glycol in the urine instead of converting it to oxalic acid. In a similar manner, methanol poisoning can be treated by ethanol administration. Retinoids participate in key developmental and cellular regulatory events largely through binding to nuclear receptors. The families of ADHs (medium-chain dehydrogenases/reductases, short-chain dehydrogenases/reductases, and aldo-keto reductases) have been implicated in key steps in the metabolism of retinol from dietary carotenoids to the transcriptional activator, retinoic acid (Gallego et al. 2006). ADH1B2 and ADH7 (ADH7 was called ADH4 in this reference) were found to have low Km (<1 mM) in an assay without added detergent (Gallego et al. 2006). The catalytic efficiencies of ADH7 and ADH1B2 are higher than that of shortchain or aldo-keto reductases (Gallego et al. 2006). A key role for ADHs in retinol oxidation is consistent with studies in knockout mice, but the effects are complex. Adh1 appears to be most important in protection against vitamin A toxicity, whereas Adh5 and Adh7 are more important in survival during multigenerational vitamin A deficiency. Production of retinoic acid from ingested retinol is decreased 90% in serum or liver of Adh1-/- mice relative to wild-type mice (Molotkov and Duester 2002; Molotkov et al. 2002c). Adh5 -/- (called Adh3 in this reference) mice show a 75% reduction in liver retinoic acid, and Adh7 -/- (called Adh4 in this reference) mice show only a 25% reduction (Molotkov et al. 2002c). Toxicity due to excess retinol was increased in adult Adh1-/- mice (LD50 was reduced threefold); there was less effect in Adh5 -/- mice (LD50 reduced 1.8-fold) or Adh7-/- mice (LD50 reduced 1.5-fold) (Molotkov et al. 2002c). A single generation of vitamin A deficiency did not affect viability, but two generations of deficiency greatly reduced viability of Adh7 -/- and Adh5 -/- mice (Deltour et al. 1999; Molotkov et al. 2002b). Wild-type and Adh1 -/- mice

were less severely affected by vitamin A deficiency (Molotkov et al. 2002b). Adh1-/-/Adh7 -/- double mutants are viable under normal laboratory conditions and are slightly less affected by two generations of vitamin A deficiency than the singly mutant Adh1-/- mice (Molotkov et al. 2002a). Ethanol and retinol metabolism interact; intoxicating doses of ethanol reduce the production of retinoic acid in serum from ingested retinol by nearly 90% in wildtype mice (Molotkov and Duester 2002). Formaldehyde is a carcinogen and potent irritant. The pathway for detoxification of formaldehyde is oxidation to the less reactive formate, a reaction catalyzed by ADH5 (formaldehyde dehydrogenase) (Holmquist and Vallee 1991) and a formylglutathione hydrolase. The reaction first involves the nonenzymatic formation of s-hydroxymethylglutathione that is oxidized to formylglutathione by ADH5 with NADþ as coenzyme. S-formylglutathione is then hydrolyzed to glutathione and formate (Sanghani et al. 2000). ADH5 participates in another key reaction, the reduction of s-nitrosoglutathione (Hedberg et al. 2003). S-nitrosoglutathione is thought to be the main nonprotein s-nitrosothiol in cells and its concentration is governed by ADH5 activity (Liu et al. 2001). Inhibition of ADH5 or snitrosoglutathione deficiency increases s-nitrosoprotein levels that can affect redox-based regulation of cellular function (Hess et al. 2005). Alterations in protein s-nitrosylation are associated with asthma, cardiovascular disease, and a growing list of path physiological conditions. 4.06.9.3 ADH Polymorphisms and Risk for Alcoholism Genetic polymorphisms that affect either the structure of the ADH isozymes or their expression in different tissues should affect the metabolism of ethanol and other alcohols and aldehydes and explain part of the difference among individuals in the risk for alcoholism and alcohol-related pathologies. Variations in ADH1B and ADH1C that affect the amino acid sequence and kinetic properties of the enzymes they encode (Table 2) are among the strongest known genetic effects on risk for alcoholism (recently reviewed in Edenberg 2007; Ehlers 2007; Eng et al. 2007; Moore et al. 2007; Scott and Taylor 2007). Much of the data come from studies of individuals from East Asia (China, Japan, and Korea) where the ADH1B2 allele, which is protective, is relatively common (Chen et al. 1996; Goedde et al.

Alcohol Dehydrogenases

1992; Tanaka et al. 1996; Thomasson et al. 1991). The mechanism of protection is believed to relate to transient (and perhaps local) increases in the rate of acetaldehyde formation due to the isozymes with higher Vmax, which produces aversive effects. In a predominantly Han-Chinese population in Taiwan, frequencies of the ADH1B2 allele encoding the high Vmax ADH1B2 and the ADH1C1 allele encoding the high Vmax ADH1C1 were both significantly lower among alcoholics than among nonalcoholics (Thomasson et al. 1991). This was confirmed for a population of Chinese in Shanghai (Chen et al. 1999). Among Chinese in Taiwan, the presence of a single ADH1B2 allele reduces risk for alcoholism by about 80%, and two ADH1B2 alleles reduces risk by nearly 90% compared to the risk for individuals in that population who are homozygous for the ADH1B1 allele (Chen et al. 1999). The strong linkage disequilibrium between ADH1B and ADH1C suggests that the apparent protective effects of ADH1C in those populations might not be an independent effect (Chen et al. 1999; Choi et al. 2005; Osier et al. 1999). ADH1B1 alleles predominate in most populations outside East Asia and the Middle East (Li et al. 2007), but despite the low allele frequency, ADH1B2 has been associated with protection from alcoholism in Europeans (Borras et al. 2000; Whitfield 2002; Zintzaras et al. 2006). ADH1B2 is present at moderate frequencies in Jewish populations, in which it is associated with reduced binge drinking (Luczak et al. 2006) and reduced risk for alcoholism (Hasin et al. 2002). Although present at low frequencies in other populations, ADH1B2 is protective against alcoholism in those populations also, but with a smaller effect than seen in East Asia (Whitfield 2002; Zintzaras et al. 2006). The difference in odds ratios for the protective effect of ADH1B2 in different populations (Whitfield 2002; Zintzaras et al. 2006) could result from differences in other polymorphisms associated with the ADH1B2 alleles, differences in the environment, or the interaction of genes and environment. ADH1B2 is associated with a lower risk for fetal alcohol syndrome in a heavy drinking culture in South Africa (Viljoen et al. 2001). ADH1C1 is protective against alcoholism in Indo-Trinidadians (Montane-Jaime et al. 2006). ADH1B3 (ADH1B369Cys) has a significant protective effect on risk for alcoholism in African Americans (Edenberg et al. 2006), Native Americans in southwest California (Wall et al. 2003), and Afro-Trinidadians (Ehlers et al. 2007) but it is rare in non-African populations. It also appears to be protective against fetal

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alcohol syndrome (Scott and Taylor 2007; Warren and Li 2005), although larger studies are needed. More comprehensive analyses of variations in the ADH genes have demonstrated that variations in ADH4 are associated with risk for alcoholism in European American families, as are noncoding variations in ADH1A and ADH1B (Edenberg et al. 2006). In case-control studies of European Americans, ADH4 has been associated with alcoholism (Luo et al. 2005, 2006a) and with drug dependence (Luo et al. 2005). A different analytical strategy demonstrated association of ADH1A, ADH1B, ADH5, ADH6, and ADH7 with alcohol dependence and/or drug dependence in European Americans and/or African Americans (Luo et al. 2006b, 2007). A case-control study drawn from Ireland showed that nine SNPs in the ADH region were associated with alcoholism; these included a coding SNP in ADH1C (rs1693482; Arg271Gln) and noncoding SNPs in ADH1A, ADH1B, and ADH5 (Kuo et al. 2008). Variations in ADH7 are associated with differences in alcohol metabolism (Birley et al. 2008). They have also been associated with risk for alcoholism when in combination with a specific haplotype at ADH1B (Osier et al. 2004). Thus many of the genes in the ADH cluster are associated with alcoholism or a related phenotype, and in non-Asian populations the associations have primarily been with noncoding SNPs. In the case of the coding SNP that defines ADH1B2, selection in East Asia has operated on a region including a potential regulatory variant in linkage disequilibrium with it (Han et al. 2007; Li et al. 2008). The data demonstrating the role of ADH genes in affecting risk for alcoholism is overwhelming, but the complexity of the association results, as well as the overlapping roles of many of the encoded enzymes in alcohol metabolism and the strong linkage disequilibrium in this region make interpretation of the roles of specific SNPs difficult. 4.06.9.4 ADH Polymorphisms and Other Diseases A related question is the effect of polymorphisms of the ADH alleles on the risk of alcoholic cirrhosis. Only a fraction of alcoholics develop cirrhosis, which has raised the question of whether part of the risk is genetic (Lumeng and Crabb 1994; Sorensen et al. 1984). A twin study suggested that genetics does play a role (Hrubec and Omenn 1981); a later study of the same population indicated that most of the genetic risk for cirrhosis was due to the genetic risk for alcoholism

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per se, although a residual independent genetic risk for cirrhosis itself remained (Reed et al. 1996). The data from several studies of the effect of ADH1B2 in Chinese or Japanese populations were inconclusive (Chao et al. 1994; Higuchi et al. 2004; Shibuya and Yoshida 1988). The effects of ADH1C polymorphisms are likewise not conclusive. In studies in Newcastle upon Tyne (Day et al. 1991) and in France (Poupon et al. 1992) the ADH1C1 allele frequencies were higher in patients with alcoholic cirrhosis or alcoholic chronic pancreatitis than in controls; the difference approached significance in the combined data (Day et al. 1993). There was evidence for association in Northern Italy (Monzoni et al. 2001). A smaller study in France did not, however, find a difference in allele frequencies (Couzigou et al. 1990), nor did a study in Spain (Vidal et al. 2004). High alcohol consumption is an important risk factor for cancers, particularly of the oral cavity, pharynx, esophagus, breast, and liver (Seitz and Becker 2007; Seitz and Stickel 2006). There is inconclusive evidence about whether variations in ADH1B and ADH1C play an independent role in increasing risk for these cancers (Brennan et al. 2004). It appears, however, that variations in the ADH genes contribute to the risk for cancers in the context of high alcohol consumption (Homann et al. 2006; Lilla et al. 2005; Seitz and Becker 2007; Seitz and Stickel 2006), a case of interaction of genes with environment. An interaction between alleles at the ADH1C gene and alcohol consumption was reported to affect risk for myocardial infarction; moderate alcohol consumption was associated with lower risk, but the effect was much stronger in men homozygous for the ADH1C2 allele (Hines et al. 2001). Moderate drinking and ADH1C2 also interacted in affecting HDL levels in men and postmenopausal women not on hormone therapy (Hines et al. 2001, 2005). The results for coronary heart disease, but not for HDL levels, were confirmed (although the effect was weaker) in a second study (Younis et al. 2005). However, the effect on HDL levels was not confirmed in an Australian study (Whitfield et al. 2003) and neither effect was confirmed in a large, epidemiological study of men in Britain and women in Wales (Ebrahim et al. 2008). Larger and more comprehensive studies of the effects of ADH genotype and alcohol consumption are needed, taking into account a much wider range of genetic variation in ADH genes.

4.06.10 Future Directions and Needs in Field Most physiological, pathological, and genetic studies to date have focused upon a few variations in two of the ADH genes, particularly the coding variations in ADH1B and ADH1C. Recent data suggest that noncoding variations play a larger role in affecting risk for alcoholism and alcohol-related diseases. Therefore, it is crucial that greater efforts go into examining a much broader range of variation: both coding and noncoding variations in all of the seven ADH genes. We need to understand the expression of these genes and how it is affected by different alleles (haplotypes) at both the RNA and protein level, including careful measurements of the actual amount of each isozyme in key tissues as a function of genetics, exposure, and disease. Because populations differ greatly in the frequencies of many of the genetic variants of ADH and also differ in diet and alcohol exposure, studies should be carried out in many populations. We need larger genetic studies that collect environmental (exposure) data, because some of the effects of variations in these genes (both protective and risk-increasing) are likely to arise only in the context of particular exposures, especially the quantity and frequency of alcohol ingestion.

Acknowledgments Related research performed in the authors’ laboratories is supported by grants from the National Institute on Alcohol Abuse and Alcoholism through grants AA006460, AA016660 and AA008401 (H. J. E.) and AA015938 and AA016301 (W. F. B.).

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