Clinical photon correlation spectroscopy evaluation of human diabetic lenses

Eq.

Eye Rrs. (1989)

Clinical

49, 241-458

Photon

SVEN-ERIK

BURSELL*~-. JOHN

Jo&n

Correlation Spectroscopy Human Diabetic Lenses RICHARD

F. HACGHTON

S. BAKER, AND

Evaluation

JEFFREY

LAWRENCE

of

N. WEISS*,

I. RAND*

Diabetes Center, 1 Jo&n Place, Boston, MA. i7.S.A ., and *Department Ophthalmology, Harvard Medical School, Boston, MA. U.S.A.

(Received 82 November

1988 a71d accepted i,n revised form I3 March

of

1989)

(Ilinical research on cataract prevention requires an in viva assessment of the lens of the eye that is non-invasive, quantitative and detects lens changes that precede lens opacification or cataract formation. The method of photon correlation spectroscopy or quasi-elastic light scattering spectroscopy provides such a non-invasive probe. The measurement, based on fluctuations in scattered light intensity caused by translational Brownian motion of the lens proteins. allows a determination of a protein diffusion coefficient and hence information on quaternary conformational changes of these protein scatterers. These protein changes have been observed in association wit,h the presence of lens opacification. The occurrence of these changes prior to opacification, however, has still to be established. The analyses performed in this study were aimed at testing the hypothesis of an association between subclinical molecular changes in the lens as measured by quasi-elastic light scattering and the presence of selected risk factors for cataract. Measurements were made from 393 diabetics attending the tIoslin Diabetes Center Eye Unit and 38 non-diabetic volunteers. Measurements at two different instrument sample times, 1.5 psec and 150 psec, allowed characterization. of two different protein size distributions contributing to the yuasi-elastically light scattered signal. Measurements performed at the 1.5 psec sample time demonstrated significantly decreased lens protein diffusivity in association with older age, higher grade of nuclear sclerosis and presence of diabetes. Statistically significant associations were also observed between lens protein diffusivity and diabetes related factors such as glycosylated hemoglobin level (diabetes control), duration of diabetes, age at onset of diabetes and type of diabetic therapy. The pattern of association exhibited between decreased protein diffusion coefficient and risk factor status is consistent with the patterns of increased risk previously demonstrated in cataract formation. Measurements performed at the 150 psec sample time demonstrated significantly decreased lens protein diffusivity in association with increasing age, female sex and giycosylated hemoglobin level. These associations differed significantly from those observed at the 1.5psec sample time, thereby suggesting that these two sample times assess different species of lens proteins. The results of this analysis demonstrate the clinical utility of quasi-elastic light scattering as a rapid, non-invasive method to quantitate lens changes and assess methods of cat,aract prevention and treatment. Key words : diabetes ; lens : prot,eins ; quasi-electric light scattering.

1. Introduction The lens of the eye is an encapsulated, avascular, continually growing tissue whose transparency is essential for normal vision. Traditional techniques for assessing lens transparency rely on slit lamp observation and photography. These techniques are subjective, difficult to quantitate and limited to the assessment of late, and often irreversible stages of the disease. At earlier stages the lens can appear perfectly clear on slit lamp observation despite significant cellular and biochemical abnormalities. Lens transparency depends on the spatial ordering of lens proteins in the lens fiber cells (Benedek, 1971). Any localized alteration in the density and/or structural t To whom all reprint MA 02215, U.S.A.

requests

should

0014-4R35/89/OX0241+

18 $03.00/O

be addressed

at Joslin

Diabetes

Center,

1 Joslin

0 1989 Academic

Place,

Boston,

Press Limited

“42

s. I‘. liI~Ii.SRI,I,

ET AI,

integrity of this ordering dur to aggregation (Specbor, l,i and Sigelman, 1974). conformational changes (Lerman and Borkman. 197X), or changes in lens hydration (Benedek et al.. 1979) cpan result in regional changes in refractive index and lens transparency. leading to the development of opacities. The assessment ofthese subtle subclinical lens changes that initiate or precede opa(Gfication thus requires a sensitivci method of in vivo detectsion. Quasi-elastic light scatt,ering (QLS) or photon correlation (PCS) has been used to investigate in vivo lens protein diffusion coefficients (Tanaka and Benedek, 1975; Tanaka and Ishimoto, 1977: Nishio et al., 1984). The efficacy of QLS as a noninvasive probe for quantitating in vivo molecular lens protein changes is well documented (Sun et al., 1984; Weiss, Rand, Gleason and Soeldner, 1984; Bursell, Weiss and Eichold, 1984a; Libondi, Magnante, Chylack and Benedek, 1986), but demonstrations or relationships between these measured protein changes and subsequent lens opacification have not been well established. If, however, molecular changes as measured using QLS can be related to the processes of oataractogenesis, then these subclinical molecular changes would be associated with specific cataractogenic risk factors during the t’ime period antecedent to the onset of clinical changes in the lens. Hypotheses

The primary purpose of this investigation is to test the hypothesis that clinical and demographic risk factors for cataract formation are associated with subclinical molecular changes in the lens as measured using QLS methodology, and further, that these associations are demonstrable prior to the clinical appearance of opacification. A second hypothesis to be tested is that measurements made at different instrument sample times can be used to investigate different lens protein species. This hypothesis is derived from the fact that the molecular constituents of the lens comprise a heterogeneous size distribution of scattering elements, and that different segments of this distribution may not be equally informative with respect to cataractogenesis and may in fact provide distinctly different information. The particular segment of this continuous size distribution of lens protein scatterers that contribute to the measured light scattered from the lens depends on the instrument sample time being used to make the measurements. The use of different sample t,imes will, theoretically, provide different measurement windows, with each window capturing information relating to a family of protein scatterers characterized by a similar effective size. For example, the use of longer sample times would characterize more slowly moving scatterers, suggestive of larger proteins or proteins’more constrained with respect to their local environment than faster moving proteins characterized using shorter instrument sample times. It is reasonable to assume that different segments of the lens protein size distribution are not equally informative with respect to cataractogenesis and may, in fact, provide distinctly different information. A two-state protein model was demonstrated in a recent study by Benedek, Chylack, Libondi, Magnante and Pennet (1987). QLS methodology was used to perform an in vivo assessment of the relative intensities (proportional to relative protein concentrations) of different’ components of the dynamically scattered laser light from the lens. The results indicated a two:state protein redistribution model in which a rapidly diffusing protein species was replaced by a slowly diffusing protein species. The redistribution of these lens protein constituents was observed to be in

NON-INVASIVE

LENS

PROTEIN

243

MEASUREMENTS

proportion to the degree of clinically evident opacification. The authors interpreted these data as representing the conversion of lens a-crystallin (the fast diffusing species) into high molecular weight aggregates (the slower diffusing species). The current investigation uses QLS scattering to quantitate the lens protein diffusion coefficients rather than to monitor changes in the concentrations of the different protein species. In these analyses, no assumptions are made concerning the relationship between the respective protein species corresponding to the two sample times used here. Indeed, there is no a priori reason to suspect that the dynamic (diffusion coefficient) characteristics of one protein specieswill be related to, or will directly influence, the diffusion coefficient of the other. Instead, those factors that influence, or are associatedwith, the occurrence of subclinical molecular changesof a given subset of lens proteins will be investigated. 2. Materials

and Methods

Instrumentation The photon biomicroscope

correlation spectroscopy system is based on a modified Haag-Streit slit lamp used to deliver incident illumination to the lens of the eye and to collect the resulting backscatteredlight. A schematic of the instrumentation is illustrated in Fig. 1. Incident illumination is provided by a 5 mW Helium/Neon laser (6323 nm). An attenuator in this light path reduces laser power.

fronrmisrion

tibrr

optic

Electronic

Slit lomp

shutter

Aperturrr

v Digit01 outocorrrlotor

Fm. 1. Schematic of the clinical discriminator,

PMT-photon

counting

photon correlation photomultiplier tube.

spectroscopy

system.

PAD-preamplifier/

244

S.-E.

KI’RSELL

ET

AI,

The beam from the laser is focused onto a 100 pm rare optical fiber using a #J x microscope objective lens. This optical fiber delivers the illumination light to the slit lamp. The output illumination from this fiber is focused to a 37 pm diameter spot in the lens of thtb eye. The power incident on the cornea is 1.5 mW. The illumination optics are mounted on the slit lamp using a third arm designed to attac.h to the central rotation axis of the slit lamp. This arm fixes the scattering angle between illumination and observation light paths at 130”. Micrometers attached to the arm allow adjustments in the vertical and axial directions in addition to rotation about. the vertic:al axis. These adjustments ensure that the laser light illumination is parfocal with the regular slit lamp illumination and observation optics. In the lens of the eye, the rapid beam divergence from the focal plane ensures a low retinal illuminance with a maximum permissible retinal exposure time of 5000 set (American National Standards Institute, 1976). The optical section of the laser beam in the lens is viewed through one of the eyepieces of the slit lamp binocular observation system. A 150 pm diameter optical fiber positioned at, the image plane of this ocular is centered over the image of the focal spot in the lens. Vertical micrometer adjustments of the incident laser beam in the lens of the eye facilitate centering the image of the focal spot over the fiber optic in the eyepiece. This optical geometry restricts the measurements to one coherence area in the lens. An aperture positioned in front of the input to the observation optics limits the collection angle and discriminates against light scattered from regions other than from the sampling site. The collection fiber optic is coupled t,o a fiber optic bundle mounted in the eyepiece. which delivers the backscattered light to a photomultiplier for detection and processing. A photon-counting photomultiplier detects the scattered light signal. The resulting photocurrent pulses are processed by a preamplifier discriminator to provide a digital photopulse output signal. A 12%channel digital autocorrelator generates the intensity autocorrelation function of this signal, which is stored temporarily in the autocorrelator. Autocorrelation functions are subsequently t,ransferred to an IBM PC for analysis. The PC controls the measurement acquisition process and stores the results on a disc in the patient’s file. The system is calibrated routinely using solutions of mirrospheres of known size.

Data analysis The light scattered from the lens is analyzed in the form of an intensity autocorrelation function using quasi-elastic light scattering spectroscopy (Cummins and Swinney, 1970). This technique measures the temporal fluctuations in scattered light intensity resulting from Brownian motion of the lens protein scattering elements. Temporal fluctuations in scattered light intensity cause proportional fluctuations in the photocurrent output of the photomultiplier. The 12%channel digital autocorrelator provides an intensity autocorrelat’ion fun&ion of these fluctuations in the form : y(T)

= (i(t)i(t+T))

(1)

for T varying from dT to 128 x dT where ( ) denotes a t,ime average. The can be chosen in a range from 100 nsec to 1 sec. In the lens, the measured autocorrelation function reflects a polydisperse of protein scatterers. The method of cumulant analysis is used to analyze (Koppel, 1972). This approach fits an equation of the form

a(T) = “l=T+{(l--~2)}P-{(r-~)“]P1/3+

.

sample

time

dT

size distribution these functions

(‘1

to the natural logarithm of the measured normalized autocorrelation function, a(T). r is the and { } denotes an average over the mean decay constant for a family of scatterers, distribution of decay times. The corresponding mean diffusion coefficient is given by D = f/p2, where Q is the amplitude of the scattering vector and depends on the scattering angle. The diffusion coefficient D describes the protein mobility and is related to the protein hydrodynamic radius R. through the Stokes-Einstein relationship (D = K,T,/GnvR, where K, is Boltzman’s constant, T, is the absolute temperature, and 7 is the viscosity of the medium). The higher order terms define the higher order moments of the distribution of scatterers such as the variance. skewness and kurtosis.

NON-INVASIVE

LENS

PROTEIN

MEASUREMENTS

245

The coefficient of the second-order term is a measure of the polydispersity or monoexponential ‘quality’ of the distribution of scatterers. This parameter, defined as

& = [{(I- -f)*)/iy*,

(3)

is the ratio of half width at half height to the average value of the distribution of decay times. For a monodisperse distribution of scatterers, & is zero as second and higher order terms in eqn (2) equal zero. The measured autocorrelation functions from the lens are analyzed using a second-order cumulant analysis. Photon counting statistical variations precluded fits to higher order cumulants. The method of cumulant analysis was chosen to analyze QLS data primarily because the cumulant algorithm is simple and fast to compute. The most accurate results are obtained when applied to a relatively narrow size distribution of unimodal scattering particles. The method of analysis also provides significant quantitative information regarding the polydispersity of the macromolecular distribution [eqn (3)]. This analysis method suffers from the disadvantage that it cannot distinguish between a broad continuous distribution and a bimodal distribution using any one sample time. If a distribution contains a significant percentage of larger aggregated particles, they act as stronger scatterers (scattering intensity proportional to the sixth power of the diameter). Thus small changes in aggregate concentration result in a dominant contribution to the scattered light signal and the autocorrelation function. Cumulant analysis makes no distinction as to the relative concentrations of particles contributing to the autocorrelation function and thus provides an average decay constant that is weighted towards the motion of the larger scatterers in the bimodal distribution. To overcome the above problem, a number of other methods of analysis have been proposed, generally aimed at characterizing bimodal distributions of scatterers. Two methods, the sum of exponential functions (Mathiez, Mouttet and Weisbuch, 1981) and the exponential sampling method (Ostrowsky, Sornette, Parker and Pike, 1981), were compared to cumulant analysis results using high concentration lens crystallin solutions (Andries and Clauwaert, 1985). There was a good agreement between the diffusion coefficient obtained from cumulant analysis and those calculated from the initial decays of the two exponential methods. The results from this comparison indicated that bimodal distributions of lens proteins can be studied using the method of cumulant analysis provided that scattered light intensity autocorrelation functions are measured at two instrument sample times, chosen judiciously, so as to window the two protein size distributions giving rise to the bimodal distribution, Cumulant analysis performed on the lens measurements demonstrated that the lens proteins existed as a polydisperse distribution of scatterers showing correlations existing over a broad range of sample times (1 psec to 1 msec). These correlations were investigated by making lens nucleus measurements over this range of sample times in six subjects. The average decay constant and & factor were obtained from four separate measurements at each of the sample times used. The results from two subjects are illustrated in Fig. 2. Typically, local minima in & were observed in the 1 psec and 100 psec sample time ranges. These minima corresponded to mean decay constants exhibiting a decreased rate of change with sample time at 1.5 psec and no change with sample time in the 100 ,usec sample time range. These results indicated that, at these sample times, the resulting autocorrelation functions more closely approximated at monodisperse population of lens protein scatterers. Thus two different lens protein size distributions could be characterized using this method of analysis. All subsequent measurements reported here were made from the lens nucleus at sample times of 1.5 psec and 150 ,usec. The scattering population that gave rise to the correlations at the 15 @see sample time exhibited much faster decay constants or diffusion coefficients (smaller protein size) than the scattering population that gave rise to the correlations at the 150 psec sample time. Patient

procedures

Diabetic population,

patients were recruited from the Joslin Diabetes Center, Beetham Eye Unit as they visited the eye clinic for regular ophthalmic examinations. Eligibility for

246

S.-E. BlTRSELL

I00

- - --a--

- _

I I - - --¤--

--

ET

AL

IO' Sample

time

Average

decay

canstanto

Average

decay

constant8

Average

quality

factor

Average

quality

factor

102

IO'

(dTksec) for for for for

31

y-old

37

y-old

31 y-old 37

y-old

non-diabetic non-diabetic non-diabetic non-diabetic

Fm. 2. Average lens nucleus decay constants (set-‘) and polydispersity at different instrument times

for two non-diabetic

sample

subjects.

this study was limited to bilaterally phakic subjects with good fixation abilities and with visual acuity correctable to 20130 or better. Exclusion criteria included previous history of eye trauma, laser therapy, ocular surgery, glaucoma or any chronic ocular condition requiring topical medication. Non-diabetic subjects recruited for this study were volunteers who fulfilled identical eligibility criteria. The clinical status of the retina was graded from retinal fundus photographs taken on the day of light scattering measurements. The lens was evaluated using dilated slit lamp biomicroscopy. Nuclear sclerosis was classified according to nuclear color on a clinical grading scale in which 0 = colorless, 1+ = very pale yellow, 2 + = pale yellow and 3 + = yellow. Cortical lens changes were classified according to extent (number of quadrants) of opacification. Subjects exhibiting nuclear sclerosis greater than 3 + or cortical lens changes greater than 2+ were excluded from the study. Interobserver variation was eliminated by restricting the lens status evaluations to the diagnosis of one observer, a clinical ophthalmologist (J. N. W.). Information concerning duration of diabetes, age at diabetes onset, diabetic therapy, current medications, hemoglobin Al status and refractive error were obtained through patient interview and by review of the Joslin Clinic records. Prior to the lens measurement, the procedure and protocol were explained to the subjects and a signed informed consent was obtained. The patients were then seated at the slit lamp with their chin and forehead positioned in the head rest. The beam from the laser was focused in the center of the lens nucleus along the visual axis. No contact lens is required for these measurements. A series of four measurements at each sample time (1.5 ,usec and 150 psec) was obtained from the lens nucleus. Each measurement lasted 5 sec. The resulting intensity autocorrelation functions were analyzed and stored together with average decay constants and the patient’s medical history in a file on the IBM PC microprocessor.

NON-INVASIVE

LENS

PROTEIN

MEASUREMENTS

247

Measurements were obtained only from the lens nucleus as in this region protein concentrations are generally homogeneous (Delaye, Clark and Benedek, 1982) whereas towards the cortical regions protein concentrations decrease rapidly. Thus small eye movements will have less effect on the measurements from the lens nucleus as sampling occurs in regions of relatively uniform protein concentration. Reproducibility At the 15ysec sample time, the standard deviation of the average decay constant obtained from the four separate measurements ranged between 5 and 10% of the average. At the 150 psec sample time the variance was generally greater, ranging between 5 and 30 % of the average value. The variation in these latter measurements was largely affected by the fixational ability of the subject. The average coefficient of variation was calculated using measurements from two nondiabetic subjects made over an 8 hr period at three separate times over a period of a month and was found to be 7 % at each of the sample times. Reproducibility was evaluated in a group of 21 diabetic subjects with ages ranging between 18 and 72 yr, in which a repeat measurement (M,) had been performed within 4 months of the initial measurement (M,), and during which time no intervening treatments had been initiated. The average time between the two measurements was 87 days. The average absolute difference between both measurements JM, -M,l was 46 % of the average of the two measurements, (M, + M,)/2, at the 1.5 psec sample time and 202 % of the average at the 15Opsec sample time. There were no significant changes in lens results with diurnal changes in intraocular pressure. Blood glucose levels, however, were found to affect the lens measurements (Bursell, Weiss and Eichold, 1984b), probably reflecting transient changes in lens cytoplasmic viscosity. The possible effects of blood glucose on the lens measurements were minimized by taking measurements at least 90 min after the subject’s last meal. Statistical analysis Univariate and multivariate analyses of the relationship between the diffusion coefficients and the continuous variables employed in the study were evaluated using simple linear regression and stepwise multiple linear regression, respectively. Tests of equality of group means among categorical and stratified continuous variables of interest were performed using a one-way analysis of covariance. Post hoc comparison among means were tested for statistical significance using a least squares means procedure. These analyses were performed using appropriate Statistical Analysis System (SAS) programs (SAS Institute, 1985). Data obtained from the left and right eyes of the same subject were highly correlated (r2 = 691 for the 1.5 psec sample time data and r2 = 696 for the 150 psec sample time data). The results in this study are thus reported with respect to the left eye only (Ray and O’Day, 1985).

3. Results Quasi-elastic light scattering measurements were obtained from the lens nucleus of 393 diabetic subjects and 38 non-diabetic volunteers. Decay constants used in the ensuing analysis represent averaged values. Statistical analyses were performed to investigate how QLS measurements might be related to clinical and demographic parameters that have previously been associated with pathogenic changes of the lens (Leske and Sperduto, 1983 ; Klein, Klein and Moss, 1985; Bar, Feller and Savir, 1983; Weale, 1980; Skalka and Prchal, 1981; Ederer, Hiller and Taylor, 1981). Analyses performed upon light scattering measurements obtained at two different instrument sample times compared light scattering information from two different measurement domains. Table I summarizes the study population with respect to clinical and demographic

24x

S.-F:. KIIRSELL

ET

TABLE

Sample

distribution

of clinical

i\L.

I

and demographic parameters clinical cataract

I)iabrtic/Non-diabetic Gender (m/f) Mean age (range) Nuclear sclerosis Diuretic therapy Steroid therapy Dilantin therapy Myopia > 2.0 diopters

previously

associated

with

393/38 234/197 41.6 yr (13-U) 31.0% 19.7% 1.7% 12% 22.9 %

parameters previously associated with clinical cataract. Sixty-five % of our study population was younger than 50 yr of age. Comparison of diabetics to non-diabetics demonstrated no significant difference in mean age (41.5 years vs. 42.7 yr). Sixty-nine % of the sample exhibited nuclear sclerosis of 1+ or less while the remaining 31% exhibited nuclear sclerosis no greater than 3+ reflecting the entry criteria of the study. Table II summarizes the distribution of diabetes-related characteristics in the study population. Ninety % of the sample had insulin-dependent diabetes and exhibited considerable heterogeneity with respect to the distribution and nature of diabetes complications (67 % exhibited some form of diabetic retinopathy). The distribution of glycosylated hemoglobin Al (HbAi), a measure of control of diabetes during the preexamination period, could be considered good to excellent in 26% of the sample (HbAl < lo), fair in 44% (10 < HbAl < 14), and poor in 30% of the sample (HbAl > 14). Decay constant

data obtained

using

the 1.5 ,usec sample

time (D1.5)

The variable most strongly correlated with the measured intensity autocorrelation function decay constants (protein diffusion coefficient) at the 1.5 psec sample time (D1.5) was age. The relationship between these two variables is illustrated in Fig. 3 for the diabetic population. The relationship between D1.5 and age for subjects less than 50 yr of age (young strata) differed significantly (P < 06001) from the relationship between D1.5 and age for subjects 50 yr of age or older (mature strata). A unit increase in age among the mature subjects produced nearly twice the decrease in decay constant that an equivalent increase in age produced among the young subjects. Regression slopes TABLE

Characteristics

II

of the diabetic

Mean duration (rang-4 Mean HgbAl (raw) Age at diagnosis < 30 Insulin therapy Percent with retinopathy

sample 155 yr (@l-55) 11.7 (6.0-18.2)

61% 90% 67

,

30

40 Age

+ 0 -

Mature 13312-158.1~ Young 10424

-93.32

50

60

70

T-,7-

80-

( Y)

X * X

were - 15&l+ 11.5 and - 93.3 + 60 for these two strata respectively. The correlation between D1.5 and age was very strong within both age strata. r2 was 059 (P = O+OOl) for the mature group and r2 was 049 (P = 00001) for the young group. Because of the strong correlation between age and the Ill.5 decay constants or protein diffusion coefficients. t,he analysis of assocsiations bet’ween D1.5 and other risk factors were a.11 adjusted for age using analysis of covariance. Adjust,ment for age eliminates apparent differences between the mean decay constant of comparison groups that might be observed solely due to differences in mean age of the groups. The highly significant difference between the mature and young age strata wit’h respect t’o the form of the Dl.5 vs. age relationship dictat,ed that adjustment for the influence of age be performed separately for these two age strata. The results of those analyses on the D1.5 decay const,ants are summarized in Tables III and IV. K’esults concerning test of association between D1.5 and selected risk factors for cataract not specifically related to diabetes are presented in Table III. Among these factors, nuclear sclerosis was t’he parameter most strongly associated with decreased D1.5 decay constants or protein diffusion coefficient’s, This phenomenon was evident across both age st’rata but’ was st)rongest among the mature group, reflecting the presence within t,his age strata of more severe lens changes. l)espit)e similar trends of association between D1.5 and nuclear sclerosis for the young and mature age strata. the absolute value of D1.5 for young and mature suh,jects exhibiting the same (Alinical nuclear sclerosis grading differed quit’e notably.

250

S.-E.

HVRSELL

ET

AL

III

TABLE

Test of association between protein diffusion coeficient measured at the 1.5 ,asec sample time (DZ.5) and clinical factors associated with cataract (adjusted for age)

strata Main

effect

Nuclear

sclerosis

Degree of freedom

Cl12*

Dilantin

1t

Gender Diuretics Steroids Myopia ( < 2 diopters)

1t I§ l,II 17

Young (F-value) [2.92] jOO5
N.S. N.S.

Mature (F-value) 542
N.S.

N.s. not significant. Variable * Nuclear sclerosis t 1 § I( 7

Dilantin Gender Diuretics Steroids Myopia

Cbmpari8on

group

Clear or 1+ NS vs. 2 + NS vs. 3 + NS [] Clear 01 i+NS vs. 2+NS Use vs. non-use Male vs. female Use vs. non-use Use vs. non-use Myopes vs. non-myopes

For example, in the group of patients exhibiting nuclear sclerosisgradings of 1 + , the average decay constants of the D1.5 data corresponding to the young group (85 subjects, mean age 345 yr) was 7253k967 set-‘, while the average of the Dl.5 data for the corresponding mature group (52 subjects, mean age 663 yr) was 4017 If: 1305 set-‘. These data indicate that although a decreased protein diffusion coefficient is correlated with increased nuclear sclerosiswithin both young and mature groups, two very different states of protein conformation and/or environment give rise to the sameclinical diagnosis. Also noted in this analysis was a large decrease in protein diffusion coefficient, among mature subjects, associated with the use of dilantin (decay constant of 2315 see-’ for users vs. 3661 see-’ for non-users). The level of significance, however, was modest due to the small number of dilantin users.Age adjusted estimates of D1.5 were not significantly associatedwith subject gender, presenceof myopia, or current use of either diuretics or steroids The results summarized in Table IV indicate that diabetes and diabetes-related parameters are more influential determinants of protein diffusion coefficients among subjects lessthan 50 yr of age than among subjects 50 yr or older. Among younger subjects, diabetics as a group manifested significantly decreaseddecay constants or protein diffusion coefficients compared to non-diabetics (P = 6036). The age adjusted mean and standard error of the mean for the young diabetic group was 7399+494 see-’ compared to 7841f 155.2set-’ for the young non-diabetic group. The increased variability in the non-diabetic group is attributable to the smaller number of subjects (27) in this group.

NON-INVASIVE

LENS

PROTEIN TABLE

251

MEASUREMENTS

IV

Test of association between protein di@km coefleient measured at the l-5 ,aaec sampEe time (Dl.5) and diabetes related characteristics associated with cataract (adjusted for age) Strata

Main

Diabetes

1*

4.42 < P < 2936 (0.01 < P < 3.04 pot < P < 4.32 (@Ol < P < 3.03 (0.01 < P < 240 (005
(001 Duration

4t

2t

Age at onset Hemoglobin Diabetic

23

Al therapy

Retinopathy

3 II

status

27

Mature (F-value)

Young (F-value)

Degree of freedom

effect

N.S.

@05) N.S.

O-05) N.S.

005) N.S.

005) N.S.

005) N.S.

N.s. not significant. Variable * Diabetes t Duration

Comparison

$ Age at onset 3 Hemoglobin Al 11 Diabetic therapy 7 Retinopathy

status

QrCnLp

Non-diabetics vs. diabetics Non-diabetics vs. O-8 yr diabetes. Mellitus (DM) vs. 9-14 yr DM vs. 1520 yr DM vs. > 20 yr DM Non-diabetics vs. onset d 30 vs. onset > 30 Non-diabetics vs. Al < median vs. Al > median Non-diabetics vs. diet controlled vs. oral hypoglycemic use vs. insulin use Non-diabetics vs. diabetics without retinopathy vs. diabetics with retinopathy

More specifically, among younger subjects, reduced protein diffusion coefficients, compared to non-diabetics, were significantly associated with glycosylated hemoglobin greater than the sample median, age of onset of diabetes after 30 yr of age, increasing duration of diabetes, and with the useof oral hypoglycemics. The presence of diabetic retinopathy exhibited only marginal correlation in this analysis f@05 < P < @I). In contrast, the mature subjects exhibited no significant difference in Dl.5 decay constants between diabetics and non-diabetics or with respect to any of the parameters related to diabetes. Decay constant

data obtained using the 150 ysec sample time (D150)

The analysis of the results obtained using the 150 psec instrument sample time (D150) were performed in a manner similar to the D1.5 analyses. The variable most highly correlated with the D150 data was again age; however, this association was very different from that observed for the Dl.5 data. In contrast to the D1.5 data, the relationship between age and D150 data was best described by a single continuous linear function. Figure 4 illustrates this- for the diabetic population. Moreover, the correlation between ageand D150 was modest (r2 = O-16)compared to the correlations

252

S.-E. BURSELL

ET

AL

160

+

+ 7

140

-

120

-

+

+

+

: P -0 ZLO E” ‘,E u .;

+ +

100

++

-

+

+

49.

t

++ +z

++

$

+

++

L

+

+++ ++

++

+ +

+

+

L.#............. 0

IO

20

30

40 Age

+ -

60

60

70

SO

(Y)

Dl60 74-36-0*5419*X

FIG. 4. Average study population.

lens decay constants at the 150 rsec sample time (D150 The solid line indicates the regression line.

se-c-‘) vs. age for the diabetic

observed for the two age strata of the D10.5 data (r2 = O-49 and r2 = 0.59). The results of the age-adjusted analyses of the D150 data are summarized in Tables V and VI. Considering those factors previously associated with clinical cataract but not with diabetes, subject gender was the only parameter that significantly correlated with the D150 data. In this case the decay constants or protein diffusion coefficients among females were lower than those among males. There were no significant correlations with nuclear sclerosis, myopia, and current use of dilantin, diuretics or systemic steroids. V

TABLE

Test of association between protein diffusion coefkient measured at the 150 psec sample time (D150) and clinical factors associated with cataract (adjusted for age)

Main

Degree of freedom*

effect

Gender Nuclear sclerosis Steroids Dilantin Diuretics Myopia ( < 2 diopters) N.S.

as in Table

III.

P>F

1

11.4

oaoo8

2

0.67 042 1.78

N.S. N.S. N.S. N.S. N.S.

1 1 1 1

not significant.

* Comparison groups

F-value

@12 @Ol

NON-INVASIVE

LENS

PROTEIN

TABLE

MEASUREMENTS

253

VI

Test of association between protein diflusion coeficient measured at the 150 psec sample time (D150) and diabetes related characteristics associated with cataract (adjusted for age)

Main ---

Degree of freedom* -___-__

effect

___Diabetes Hemoglobin A1 Duration $ge on onset Diabetic therapy Retinopathy status not significant. * Comparison groups

1 2 4 2 3 2

F-value 0.33 3.10 0.55 0.24 0.70 0.61

P>F N.S. 0.046 N.S. N.S. N.S. N.S.

N.S.

as in Table

IV.

Among those parameters related to diabetes, only glycosylated hemoglobin was significantly correlated with D150 data. The D150 data were not correlated with diabetes itself nor with any parameter associated with diabetes, other than glycosylated hemoglobin. The DE0 data for poorly controlled diabetics and for nondiabetics were similar, but among diabetics with good to excellent control of diabetes the Dl50 data were significantly increased in comparison both to poorly controlled diabetes and to non-diabetes. The relationships noted for the D150 data were different from those observed for the D1.5 data, where there was a significantly decreased decay constant in the group of poorly controlled diabetics compared to non-diabetics, 4. Discussion

Significant associations have been demonstrated between subclinical protein changesin the human lens as measuredin vivo by QLS and several known risk factors for cataractogenesis. These data support the contention that the observed molecular changesoccur prior to the onset of cataract formation and therefore may be involved in, or associated with, the actual processof cataractogenesis. In addition, it has been shown that the diffusion coefficients derived from the QLS measurementsare dependent upon the sample time used. The relationship between protein diffusion coefficient and risk factor status among the family of proteins measured at the 1.5 ,usecsample time differed significantly from the relationships observed using the 150,usecsampletime. This finding is not unexpected asone would not expect the entire spectrum of lens proteins to be equally contributory to the cataractogenic process. It is also unlikely that risk factor status would impact equivalently upon each protein species. Moreover, because cataractogenesis is multifactorial in nature, one can postulate a multi-stage cataractogenic process involving intermediate speciesof protein molecules. If this is the casethen it is likely that the influence of a given determinant upon protein diffusion coefficient will be dependent on the stage of the process or equivalently, the protein species being assessed. The proteins measured at the 1.5 psec sample time, in the young group, showed decay constants giving rise to diffusion coefficients in the range between 1.6 x lo-’ cm2

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sec.- ’ and 6.4 x 10e8 cm2 sect’. The corresponding range in hydrodynamic radii for these proteins is between 135 and 300 A, which is comparable in size to lens TV crystallin monomeric and smaller aggregated units and agrees well with ot,her published data (Benedek et al.. 1987; Siezen and Owen, 1983: Siezen, Bindels and Hoenders, 1979). One must bear in mind, however, t,hat the hydrodynamic radii calculated here are affected by protein-protein interactions and as such represent the upper limit of the size distribution (Phillies, Benedek and Mazer, 1976). In older subjects, cal:ulated hydrodynamic radii from the D1.5 data ranged between 300 and 7000 A. These larger lens scattering proteins have also been measured in the,human lens (Bettelheim, Siew and Chylack, 1981) using measurements of the angular distribution of polarized and depolarized light, from thin lens sections. The decrease in the D1.5 data with age reflects a conversion of smaller faster diffusing a-crystallin units into higher molecular weight aggregates. This interpretation is based on the increased scattering efficiency of lens protein aggregates and the characteristics of cumulant’ analysis. As the larger aggregates scatter a larger fraction of the incident, light, relatively minor increases in the concentration of these species can have a dominant effect on the measured intensity autocorrelation function. Cumulant analysis cannot distinguish between the contributions from the smaller and larger scatterers and so the analysis weights the calculated decay constant. Thus it reflects the dominating contributor to the scattered light signal, in this case the larger aggregated proteins, and the decreasing decay constant at the 1.5 ,usec sample time reflects an increasing concentration of larger aggregated a-crystallin protein units. This observation is consistent with biochemical studies showing a gradual disappearance of a-crystallin monomers in the aging lens nucleus (McFall-Ngai, Ding, Takemoto and Horwitz, 1985). The scattered light contributions from p- and a-crystallins in the lens are negligible compared to light scattered from the a-crystallins as the former crystallins are considerably smaller in size. Considering the D150 data, the calculated molecular sizes range between 10000 and 70000 A, which is comparable to the width of the lens fiber cell itself. In this case, it is probably unrealistic to refer to a molecular size related to this slowly decaying component of the scattered light signal. The relaxations giving rise to this slowly decaying component could result from constrained membrane-bound proteins or from concentration fluctuations of the lens fiber cytoplasmic gel matrix (Tanaka, Hacker and Benedek, 1973). Further investigation is needed to resolve the exact, origin of these slowly decaying correlations at the 150,usec sample time. The decreased diffusion coefficient of proteins measured at the 1.5 ,usec sample time was significantly associated with increasing age, the presence of diabetes and increased nuclear sclerosis. Notably, the patterns of association exhibited by protein diffusion at this sample time are consistent with patterns of risk exhibited by respective risk factors for cataract formation. The concordance between protein diffusion and risk factor status exhibited by these data demonstrate that the relationships observed in this analysis represent clinically significant physicochemical processes rather than chance statistical associations. The particular relationship between protein diffusion and age described in this analysis has not been previously reported. The significant difference in the relationship between protein diffusion and increasing age for subjects 50 yr of age or greater compared to subjects less than 50 yr of age is consistent with the relatively infrequent occurrence of senile cataract prior to age 50 and the abrupt increase in frequency

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thereafter. The accelerated rate of change of protein diffusion coefficients in older subjects may relate to alterations in metabolism or in hormonal and enzymatic homeostasis (associated with advancing age) which on achieving a threshold, accelerates the physico-chemical processes responsible for conformational changes of the protein molecule. Another possibility is that protein diffusivity is altered secondary to changes in the local environment of the proteins, leading to the phenomena observed in cold cataracts related to the occurrence of phase change transitions of the aging lens gel matrix (Benedek et al., 1987; Latina et al., 1987). This study indicated that the influence of diabetes and diabetes-related parameters on protein diffusion was significantly greater among young subjects than among subjects 50 yr of age or older. This is an important finding and is consistent with the fact that cataract was found to be a significant cause of blindness in younger onset diabetic subjects (Klein et al., 1985). The exclusion of subjects who had already progressed to visually significant lesions of the lens undoubtedly led to an underestimation of the effect of diabetes on lens protein diffusion in the group of mature diabetics and diabetics exhibiting long durations of diabetes. The impact of this potential source of bias is difficult to estimate. The results of this study, however, are in excellent agreement with populationbased epidemiological studies demonstrating significantly earlier onset of cataract in diabetics compared to non-diabetics, with a progressively diminishing difference in risk of cataract between these groups with advancing age (Leske and Sperduto, 1983 ; Ederer et al., 1981). The pattern of associations observed between protein diffusion and such diabetes-related parameters as glycosylated hemoglobin (diabetes control), diabetic therapy, age at diabetes onset, and duration of diabetes were all consistent with previously published epidemiological associations relating diabetic parameters to the risk of cataract formation (Klein et al., 1985; Skalka and Prchal, 1981). This correspondenceof results lends further support to the claim that these data reflect a clinically significant physico-chemical process. The pattern of association observed between nuclear sclerosisand protein diffusion coefficients is perhaps the most provocative and interesting finding in this study. Nuclear sclerosisis commonly cited as an index of severity of cataract formation. Chylack, Ransil and White (1984), however, have demonstrated that, although on average the increased nuclear yellowing is associated with increased nuclear opacification, the degreeof nuclear yellowing is in itself a poor predictor of the extent of nuclear opacification. Thus, despite their association with one another, these two entities appear to represent often concurrent but distinctly different physiological processes. A similar relationship appears to be operative between nuclear yellowing and protein diffusion. In this study nuclear yellowing and lensprotein diffusion coefficients were significantly correlated. The marked difference, however, in the mean protein diffusion manifested by the young subjects compared to the mature subjects exhibiting the same clinical lens grade suggeststhat protein diffusion is not directly related to the processof nuclear yellowing but instead is a measure of an associated process. The analyses here were age adjusted. Thus, the association between nuclear yellowing and protein diffusivity cannot be explained secondary to their common association with age. Instead it suggests that the relationship between nuclear yellowing and protein diffusion represents the relationship between nuclear yellowing and lensnuclear opacification processes.A comparison of the relative abilities of these

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two measures to predict nuclear opacification would be a hypothesis to be tested in future investigations. The decreased diffusion measured at the 150 ,uBec sample time was significantly correlated with age, female sex, and decreased glycosylated hemoglobin among diabetics. Only two parameters (age and glycosylated hemoglobin) were significantly associated with diffusion coefficient at both the 1.5 and 150 ,usec sample times. Furthermore, the relationship between diffusion and these two parameters differed markedly for measurements made at the 150 psec sample time compared to those made at the 1.5 psec sample time. These data clearly indicate that the information obtained about the lens proteins from measurements made at these two sample times differ significantly. Evidence in support of an association between diffusion coefficients measured at the 150 psec sample time and risk of cataract is less compelling than that observed for measurements performed at the l-5 psec sample time. Both female sex and increasing age have been cited as risk factors for cataract (Leske and Sperduto, 1983 ; Klein et al., 1985): however, the relationship between diffusion coefficient and age at, this sample time was relatively weak and did not manifest the greater strength of association one would expect among the older subjects. The pattern of associations exhibited between glycosylated hemoglobin and protein diffusion at this sample time was not consistent with the pattern of cataract risk exhibited for glycosylated hemoglobin in epidemiological studies. This observation, together with the absence of a demonstrated association between diabetes and diffusion coefficient measured at this sample time, suggests that this result may represent a spurious finding. Finally, these anlyses were unable to demonstrate significant associations between QLS measurements and myopia, diuretic use and systemic steroid use. This does not. diminish the validity of our findings, and the absence of any associations could be due to any one of several possibilities. For example, the primary site of action of systemic steroid use in the lens is in the lens posterior cortex, and as measurements here were performed exclusively from the lens nucleus, it is perhaps not surprising that this association was not demonstrated. Another consideration is the choice of sample times. If the observed effect of these risk factors manifested in a protein species that was not well characterized at the sample times used here, then measurement sensitivity to these changes would be decreased and may explain the lack of association. The results obtained from this study demonstrates that the QLS methodology provides an objective non-invasive tool for quantitating lens protein status in a clinical setting. This technique provides information on preclinical changes in lens protein conformation and/or environment. The data presented here suggest that QLS is potentially useful for investigating the molecular mechanisms associated with cataractogenesis. Current efforts now focus on demonstrating the diagnostic utility of the technique in the longitudinal assessment of lens protein changes. ACKNOWLEDGMENTS This work was supported in part by the National Eye Institute grant EY05278 and by the Massachusetts Lions Eye Research Fund Inc. Special thanks to Jonathan A. Spencer for his editorial contributions.

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