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Understanding genetics of glucose and insulin dynamics in Mexican American individuals from Starr County, Texas. M. Karhade, G. Jun, L.E. Petty, G. Bell, J.E. Below, C.L. Hanis Diabetes is the fastest growing epidemic Currently 86 million Americans (39.3%) have pre- diabetes Estimated worldwide prevalence of 592 million by 2035 Diabetes remains the 7 th leading cause of death in United States Rate of diabetes is much higher in Mexican Americans (13.9%) compared to non-Hispanic whites (7.6%) Number of loci associated with diabetes: 120 (~150 variants) Less than 20% of the heritability explained Markers for type 2 diabetes (T2D) are not satisfactory Insulin resistance (IR) develops long before T2D develops IR is can be measured from oral glucose tolerance test (OGTT) (Image 1) 331 previously undiagnosed, unrelated Hispanic subjects from Starr County OGTT challenge 75 gm. of glucose after 8hr or overnight fast. Blood samples were collected at 0, 10, 20, 30, 60, 90 and 120 minutes. Whole genome sequencing (WES) data was collected using Agilent Truseq capture reagents on Illumina HiSeq2000 & GWAS array data was collected using Genome-Wide Human SNP Array 6.0 Affymetrix Phasing was done using SHAPEIT & imputation was done using IMPUTE-2 SNPTEST v2.4-beta was used to analyze Imputed GWAS data (QC > 0.8) EPACTS pipeline was used to analyze WES data (MAC > 5) SKAT-O was used for gene-wise test (MAF < 5%) Phenotypes were adjusted for age, BMI and population substructure Image 1: Oral Glucose tolerance test rs75439564 (ST18; p-value 1.87x10 -8 ) was found to be associated with blood insulin levels at 10 minutes post OGTT in exome-wide single variant. Fitted trajectories insulin (left) and glucose (right) below. (RED: carriers) An initial observation in the 1970s that Starr County, Texas, had the highest diabetes-specific mortality of any of the 254 Texas counties led to the establishment of a field office in Rio Grande City, Texas (the county seat of Starr County) and the initiation of a series of studies to understand the epidemiology and genetics of type 2 diabetes, its complications and related conditions in this predominantly (97%) Mexican American population. The field office opened in February 1981 and has operated continuously since then. During this time, three systematic surveys of the population have been conducted as well as family and longitudinal studies. Culturally sensitive diabetes education programs have been developed and implemented as well as a weight loss intervention. In total, more than 23,000 Mexican American individuals have been examined with more than 200,000 aliquots of biological specimens stored. Collectively, these studies are known as the Starr County Health Studies. The present Genetics of Diabetes Study has the goal of identifying loci/alleles that underlie susceptibility to type 2 diabetes in this high risk population using genome wide markers and association testing. The study makes use of two primary resources that have been developed in order to identify 1,000 type 2 diabetes cases and 1,000 disease free controls. Gene based test: Protein altering mutation (n=331) Ch r Gene BP- Start BP-end p-value Trait Passi ng Singl et Known association Ref 9 CERCAM 1311846 0 13119815 5 4.95E-06 BCL 0 to 10 min 8 4 Methylation in Obese 7 10 USP54 7525842 5 75296201 3.71E-06 BGL 30 to 60 min 7 5 Apoptosis in islets 8 8 ZFHX4 7761635 1 77776358 4.19E-06 BIL 10 to 20 min 23 12 Hypothyroidism 9 8 EPHX2 2735849 5 27362511 6.65E-06 C-peptide baseline 3 1 Candidate for CVD 10 Insulin 10 min Change in Blood C-peptide from baseline to 10 min Change in Blood C-peptide from 20 to 30 min Change in Blood glucose from 10 to 20 min Single variant test (n=331) Ch r SNPs Gene Type BP p value TRAIT Known association Ref 8 rs754395 64 ST18 Synonymous 5308457 5 1.87E-08 BIL at 10 min β-cell apoptosis 1 8 rs754395 64 ST18 Synonymous 5308457 5 7.91E-08 BCL at 10 min β-cell apoptosis 1 8 rs754395 64 ST18 Synonymous 5308457 5 1.78E-07 BCL 0 to 10 min β-cell apoptosis 1 16 rs171370 53 NMRALI 5' UTR 4524155 2.85E-07 BIL 20 to 30 min Adipokines production 3 16 rs25685 HMOX2 Synonymous 4556911 4.95E-07 BIL 20 to 30 min Complications with T2D 6 8 rs170536 12 DOCK5 Intron 2526128 1 1.94E-06 BGL 10 to 20 min VNTR severe obesity 4 10 rs118135 97 C10orf1 20 Synonymous 1244591 39 2.08E-06 BIL 20 to 30 min none 16 rs719145 8 NMRALI 3' UTR 4511752 2.41E-06 BIL 20 to 30 min Adipokines production 3 Methods The Starr County Results Introduction Significance Our study focuses on the early changes of metabolism in normoglycemic individuals. Criteria for diagnosis of diabetes is fasting blood glucose >=125 mg/dl (pre-diabetes >=100 mg/dl to <125mg/dl) and 2hr post-glucose challenge >=200 mg/dl (pre-diabetes >=140 mg/dl to <200mg/dl) and/or hemoglobin A1c (HbA1c) of ≥6.5% (pre- diabetes >=5.7 to <6.4%) Pathophysiology is a continuous process but not the diagnostic criteria OGTT provides the best representation of physiological variation in the parameters to be tested as compared to the clamp techniques. Insulin resistance is an excellent marker for future development T2D (approximately 5-10 years before T2D). Oral glucose tolerance test (OGTT) provides excellent opportunity to analyze changes in the glucose, insulin, c-peptide, pro-insulin etc. over two or more hours after oral glucose challenge. Future directions We are currently exploring surrogate markers of insulin resistance such as glucose/insulin ratio, insulinogenic index, HOMA-IR, HOMA-%B, HOMA β-cell, QUICKI, glucose insulin (GI) product, fasting insulin resistance index, Matsuda index, Gutt index, Stumvoll index, log(HOMA-IR) We plan to extend analysis of OGTT as a curve rather than seven discrete time-points using functional analysis. We plan to use minimum modeling approach to characterize glucose insulin dynamics and test effect of genetics on those parameters. Larger study samples and replication studies are necessary to ascertain our positive findings. 1. Henry, C.The Journal of Biological Chemistry, (2014) 2. Antoni Castro. Atherosclerosis, Vol 209, Issue 1, 201-205 (2010) 3. Freyhaus, H. . Cell Metabolism, 16(1), 81–89 (2012) 4. El-Sayed Moustafa Hum Mol Gen, 21(16), 3727– 3738 (2012) 6. Nowak, W. N. Jrnl of Diab Investigation, 5(1), 99–107 (2014) 7. Markus Sällman Almén Genomics, Volume 99, Issue 3 (2010) 8. Cnop, Diabetes, 63(6), 1978-1993 (2014) 9. Gudbjartsson, D. F. Nat Genet, 40(5), 609- 615 (2008) 10. Burdon, K. P. . Diab Vasc Dis Res, 5(2), References

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Understanding genetics of glucose and insulin dynamics in Mexican American individuals from Starr County, Texas.

M. Karhade, G. Jun, L.E. Petty, G. Bell, J.E. Below, C.L. Hanis

• Diabetes is the fastest growing epidemic• Currently 86 million Americans (39.3%) have pre-diabetes• Estimated worldwide prevalence of 592 million by 2035• Diabetes remains the 7th leading cause of death in United States• Rate of diabetes is much higher in Mexican Americans (13.9%) compared to

non-Hispanic whites (7.6%)• Number of loci associated with diabetes: 120 (~150 variants)• Less than 20% of the heritability explained• Markers for type 2 diabetes (T2D) are not satisfactory• Insulin resistance (IR) develops long before T2D develops• IR is can be measured from oral glucose tolerance test (OGTT) (Image 1)

• 331 previously undiagnosed, unrelated Hispanic subjects from Starr County• OGTT challenge 75 gm. of glucose after 8hr or overnight fast.• Blood samples were collected at 0, 10, 20, 30, 60, 90 and 120 minutes.• Whole genome sequencing (WES) data was collected using Agilent Truseq

capture reagents on Illumina HiSeq2000 & GWAS array data was collected using Genome-Wide Human SNP Array 6.0 Affymetrix

• Phasing was done using SHAPEIT & imputation was done using IMPUTE-2• SNPTEST v2.4-beta was used to analyze Imputed GWAS data (QC > 0.8)• EPACTS pipeline was used to analyze WES data (MAC > 5)• SKAT-O was used for gene-wise test (MAF < 5%)• Phenotypes were adjusted for age, BMI and population substructure

Image 1: Oral Glucose tolerance test

rs75439564 (ST18; p-value 1.87x10-8) was found to be associated with blood insulin levels at 10 minutes post OGTT in exome-wide single variant. Fitted trajectories insulin (left) and glucose (right) below. (RED: carriers)

An initial observation in the 1970s that Starr County, Texas, had the highest diabetes-specific mortality of any of the 254 Texas counties led to the establishment of a field office in Rio Grande City, Texas (the county seat of Starr County) and the initiation of a series of studies to understand the epidemiology and genetics of type 2 diabetes, its complications and related conditions in this predominantly (97%) Mexican American population. The field office opened in February 1981 and has operated continuously since then. During this time, three systematic surveys of the population have been conducted as well as family and longitudinal studies. Culturally sensitive diabetes education programs have been developed and implemented as well as a weight loss intervention. In total, more than 23,000 Mexican American individuals have been examined with more than 200,000 aliquots of biological specimens stored. Collectively, these studies are known as the Starr County Health Studies.

The present Genetics of Diabetes Study has the goal of identifying loci/alleles that underlie susceptibility to type 2 diabetes in this high risk population using genome wide markers and association testing. The study makes use of two primary resources that have been developed in order to identify 1,000 type 2 diabetes cases and 1,000 disease free controls.

Gene based test: Protein altering mutation (n=331)Chr Gene BP-Start BP-end p-value Trait Passing Singlet Known association Ref

9 CERCAM 13118460 131198155 4.95E-06 BCL 0 to 10 min 8 4 Methylation in Obese 7

10 USP54 75258425 75296201 3.71E-06 BGL 30 to 60 min 7 5 Apoptosis in islets 8

8 ZFHX4 77616351 77776358 4.19E-06 BIL 10 to 20 min 23 12 Hypothyroidism 9

8 EPHX2 27358495 27362511 6.65E-06 C-peptide baseline 3 1 Candidate for CVD 10

Insulin 10 min

Change in Blood C-peptide from baseline to 10 min

Change in Blood C-peptide from 20 to 30 min

Change in Blood glucose from 10 to 20 min

Single variant test (n=331)Chr SNPs Gene Type BP p value TRAIT Known association Ref

8 rs75439564 ST18 Synonymous 53084575 1.87E-08 BIL at 10 min β-cell apoptosis 1

8 rs75439564 ST18 Synonymous 53084575 7.91E-08 BCL at 10 min β-cell apoptosis 1

8 rs75439564 ST18 Synonymous 53084575 1.78E-07 BCL 0 to 10 min β-cell apoptosis 1

16 rs17137053 NMRALI 5' UTR 4524155 2.85E-07 BIL 20 to 30 min Adipokines production 3

16 rs25685 HMOX2 Synonymous 4556911 4.95E-07 BIL 20 to 30 min Complications with T2D 6

8 rs17053612 DOCK5 Intron 25261281 1.94E-06 BGL 10 to 20 min VNTR severe obesity 4

10 rs11813597 C10orf120 Synonymous 124459139 2.08E-06 BIL 20 to 30 min none

16 rs7191458 NMRALI 3' UTR 4511752 2.41E-06 BIL 20 to 30 min Adipokines production 3

Methods

The Starr County

Results

Introduction

Significance• Our study focuses on the early changes of metabolism in normoglycemic

individuals.• Criteria for diagnosis of diabetes is fasting blood glucose >=125 mg/dl (pre-

diabetes >=100 mg/dl to <125mg/dl) and 2hr post-glucose challenge >=200 mg/dl (pre-diabetes >=140 mg/dl to <200mg/dl) and/or hemoglobin A1c (HbA1c) of ≥6.5% (pre-diabetes >=5.7 to <6.4%)

• Pathophysiology is a continuous process but not the diagnostic criteria• OGTT provides the best representation of physiological variation in the

parameters to be tested as compared to the clamp techniques.• Insulin resistance is an excellent marker for future development T2D

(approximately 5-10 years before T2D).• Oral glucose tolerance test (OGTT) provides excellent opportunity to analyze

changes in the glucose, insulin, c-peptide, pro-insulin etc. over two or more hours after oral glucose challenge.

Future directions• We are currently exploring surrogate markers of insulin resistance such as

glucose/insulin ratio, insulinogenic index, HOMA-IR, HOMA-%B, HOMA β-cell, QUICKI, glucose insulin (GI) product, fasting insulin resistance index, Matsuda index, Gutt index, Stumvoll index, log(HOMA-IR)

• We plan to extend analysis of OGTT as a curve rather than seven discrete time-points using functional analysis.

• We plan to use minimum modeling approach to characterize glucose insulin dynamics and test effect of genetics on those parameters.

• Larger study samples and replication studies are necessary to ascertain our positive findings.

1. Henry, C.The Journal of Biological Chemistry, (2014)2. Antoni Castro. Atherosclerosis, Vol 209, Issue 1, 201-205 (2010)3. Freyhaus, H. . Cell Metabolism, 16(1), 81–89 (2012)4. El-Sayed Moustafa Hum Mol Gen, 21(16), 3727–3738 (2012)5. Yoshida, T. Intl Journal of Molecular Med, 25, 281-286 (2010)

6. Nowak, W. N. Jrnl of Diab Investigation, 5(1), 99–107 (2014)7. Markus Sällman Almén Genomics, Volume 99, Issue 3 (2010)8. Cnop, Diabetes, 63(6), 1978-1993 (2014)9. Gudbjartsson, D. F. Nat Genet, 40(5), 609-615 (2008)10. Burdon, K. P. . Diab Vasc Dis Res, 5(2), 128-134 (2008)

References