AltshulerPublicationsSunAMPK

HAPLOTYPE STRUCTURES AND LARGE-SCALE ASSOCIATION TESTING OF THE 5’ AMP-ACTIVATED PROTEIN KINASE (AMPK) GENES PRKAA2, PRKAB1 AND PRKAB2 WITH TYPE 2 DIABETES

¹Departments of Molecular Biology and ⁷Medicine, Massachusetts General Hospital, Boston, Massachusetts; ²Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Departments of ³ Endocrinology and ⁴ Clinical Science, University Hospital MAS, Lund University, Malmö, Sweden; ⁵ Department of Medicine, Helsinki University Central Hospital; Folkhalsan Genetic Institute, Folkhalsan Research Center; and Research Program for Molecular Medicine, University of Helsinki, Helsinki, Finland; ⁶ University of Montreal Community Genomic Center, Chicoutimi Hospital, Quebec, Canada; ⁸Divisions of Genetics and Endocrinology, Children’s Hospital, Boston, Massachusetts; and Departments of ⁹Genetics and¹⁰Medicine, Harvard Medical School, Boston, Massachusetts

(†) Current affiliation: UC Davis School of Medicine, Sacramento, California

(‡) Current affiliation: Department of Systems Biology, Harvard Medical School and Division of Signal Transduction, Beth Israel Deaconess Medical Center, Boston, MA

AMP-activated protein kinase (AMPK) is a key molecular regulator of cellular metabolism, and its activity is induced by both metformin and thiazolidinedione anti-diabetic medications. It has therefore been proposed both as a putative agent in the pathophysiology of type 2 diabetes and as a valid target for therapeutic intervention. Thus, the genes that encode the various AMPK subunits are intriguing candidates for the inherited basis of type 2 diabetes. We therefore set out to test for the association of common variants in the genes that encode three selected AMPK subunits with type 2 diabetes and related phenotypes.

Of the seven genes that encode AMPK isoforms, we initially chose PRKAA2, PRKAB1, and PRKAB2 because of their higher prior probability of association with type 2 diabetes, based on previous reports of genetic linkage, functional molecular studies, expression patterns and pharmacological evidence. We determined their haplotype structure, selected a subset of tag single nucleotide polymorphisms that comprehensively capture the extent of common genetic variation in these genes, and genotyped them in family-based and case/control samples comprising 4,206 individuals. Analysis of single-marker and multi-marker tests revealed no association with type 2 diabetes, fasting plasma glucose or insulin sensitivity. Several nominal associations of variants in PRKAA2 and PRKAB1 with body mass index appeared to be consistent with statistical noise.

Supplementary Figure 1A - Figure 1C:
Fig. 1A-C: Linkage disequilibrium (LD) plot across the AMPK genes PRKAA2 (A), PRKAB1 (B) and PRKAB2 (C) loci. In each figure, the horizontal black line depicts the chromosomal segment analyzed in our CEU sample. The SNP locations are indicated by hatch marks above the black line: successful SNPs from dbSNP are depicted in black, the SNPs downloaded from the HapMap are in blue and the tag SNPs are in green. An LD plot is depicted in the bottom part of the figure based on the measure D’: each square represents the magnitude of LD for a single pair of markers, with red color indicating LD that is strong (D’ >0.8) and statistically significant (LOD >2.0). The haplotypes spanning this block are shown above the LD plot, with the thickness of the blue line indicating their frequency in the CEPH reference sample (figure prepared using the program LocusView v2.0, T. Petryshen, A. Kirby, M. Ainscow, unpublished software).

Supplementary Table 1: Genotype counts for all sub-samples
Allele counts for each of the 22 single-marker (top panel of each gene) and 18 multi-marker (bottom panel of each gene) tests in our diabetic subsamples; within each SNP, the major allele is presented first. Multi-marker haplotypes were assigned probabilities according to an expectation-maximization algorithm as implemented in Haploview, and are compared versus all other possibilities at those loci (see text for details). T, transmitted; U, untransmitted.

Supplementary Table 2: Correlation of PRKAA2, PRKAB1 and PRKAB2 SNPs to tagging tests selected by Tagger
The Tagger algorithm (http://www.broad.mit.edu/mpg/tagger) was used to select single- and multi-marker tests to capture all SNPs of minor allele frequency (MAF) ³5% with an r² ³0.8 in PRKAA2, PRKAB1 and PRKAB2 (see text for details). One SNP located >33 kb downstream from the end of PRKAB1 (rs278121) and two SNPs located >8 kb downstream from the end of PRKAB2 (rs2077749 and rs720609) were less well captured at r² =0.69 and 0.60, respectively.

Supplementary Table 3: Association of variants in PRKAA2¸ PRKAB1 and PRKAB2 with quantitative traits
Fasting plasma glucose (mmol/L) and the whole-body insulin sensitivity index (ISI) (47) were determined in 756 non-diabetic Scandinavian subjects (363 female). The latter was logarithmically transformed; values are mean ± SD (where SD = 0 indicates a single observation). These measures were compared by ANOVA depending on each of 22 single-marker and 18 multi-marker genotypic tests. The SNPs that define each multi-marker test (bottom panel for each gene) are numbered as in the top panel, and correspond to those in Table 2. M/M, homozygotes for the major allele; M/m, heterozygotes; m/m, homozygotes for the minor allele. 1 1, two copies of the multi-marker haplotype; 1 2, one copy of the multi-marker haplotype; 2 2, zero copies of the multi-marker haplotype. The only two nominally significant P values (*) are not reliable due to the low number of observations (N=2) in the outlier cells.





					This site contains online supplementary data for our manuscript, HAPLOTYPE STRUCTURES AND LARGE-SCALE ASSOCIATION TESTING OF THE 5’ AMP-ACTIVATED PROTEIN KINASE (AMPK) GENES PRKAA2, *PRKAB1* AND *PRKAB2* WITH TYPE 2 DIABETES Maria W. Sun ^1,2 (†), Jennifer Y. Lee ^1,2 (‡), Paul I.W. de Bakker ^1,2,9, Noël P. Burtt ², Peter Almgren ³, Lennart Råstam⁴, Tiinamaija Tuomi ⁵, Daniel Gaudet ⁶, Mark J. Daly ^2,7, Joel N. Hirschhorn ^2,8,9, David Altshuler ^1,2,7,9,10, Leif Groop ^3,5 and Jose C. Florez ^1,2,7,10 ¹Departments of Molecular Biology and ⁷Medicine, Massachusetts General Hospital, Boston, Massachusetts; ²Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Departments of ³ Endocrinology and ⁴ Clinical Science, University Hospital MAS, Lund University, Malmö, Sweden; ⁵ Department of Medicine, Helsinki University Central Hospital; Folkhalsan Genetic Institute, Folkhalsan Research Center; and Research Program for Molecular Medicine, University of Helsinki, Helsinki, Finland; ⁶ University of Montreal Community Genomic Center, Chicoutimi Hospital, Quebec, Canada; ⁸Divisions of Genetics and Endocrinology, Children’s Hospital, Boston, Massachusetts; and Departments of ⁹Genetics and¹⁰Medicine, Harvard Medical School, Boston, Massachusetts (†) Current affiliation: UC Davis School of Medicine, Sacramento, California (‡) Current affiliation: Department of Systems Biology, Harvard Medical School and Division of Signal Transduction, Beth Israel Deaconess Medical Center, Boston, MA ABSTRACT AMP-activated protein kinase (AMPK) is a key molecular regulator of cellular metabolism, and its activity is induced by both metformin and thiazolidinedione anti-diabetic medications. It has therefore been proposed both as a putative agent in the pathophysiology of type 2 diabetes and as a valid target for therapeutic intervention. Thus, the genes that encode the various AMPK subunits are intriguing candidates for the inherited basis of type 2 diabetes. We therefore set out to test for the association of common variants in the genes that encode three selected AMPK subunits with type 2 diabetes and related phenotypes. Of the seven genes that encode AMPK isoforms, we initially chose PRKAA2, PRKAB1, and PRKAB2 because of their higher prior probability of association with type 2 diabetes, based on previous reports of genetic linkage, functional molecular studies, expression patterns and pharmacological evidence. We determined their haplotype structure, selected a subset of tag single nucleotide polymorphisms that comprehensively capture the extent of common genetic variation in these genes, and genotyped them in family-based and case/control samples comprising 4,206 individuals. Analysis of single-marker and multi-marker tests revealed no association with type 2 diabetes, fasting plasma glucose or insulin sensitivity. Several nominal associations of variants in PRKAA2 and PRKAB1 with body mass index appeared to be consistent with statistical noise. Online supplementary information Supplementary Figure 1A - Figure 1C: Fig. 1A-C: Linkage disequilibrium (LD) plot across the AMPK genes PRKAA2 (A), PRKAB1 (B) and PRKAB2 (C) loci. In each figure, the horizontal black line depicts the chromosomal segment analyzed in our CEU sample. The SNP locations are indicated by hatch marks above the black line: successful SNPs from dbSNP are depicted in black, the SNPs downloaded from the HapMap are in blue and the tag SNPs are in green. An LD plot is depicted in the bottom part of the figure based on the measure D’: each square represents the magnitude of LD for a single pair of markers, with red color indicating LD that is strong (D’ >0.8) and statistically significant (LOD >2.0). The haplotypes spanning this block are shown above the LD plot, with the thickness of the blue line indicating their frequency in the CEPH reference sample (figure prepared using the program LocusView v2.0, T. Petryshen, A. Kirby, M. Ainscow, unpublished software). Supplementary Table 1: Genotype counts for all sub-samples Allele counts for each of the 22 single-marker (top panel of each gene) and 18 multi-marker (bottom panel of each gene) tests in our diabetic subsamples; within each SNP, the major allele is presented first. Multi-marker haplotypes were assigned probabilities according to an expectation-maximization algorithm as implemented in Haploview, and are compared versus all other possibilities at those loci (see text for details). T, transmitted; U, untransmitted. Supplementary Table 2: Correlation of PRKAA2, PRKAB1 and PRKAB2 SNPs to tagging tests selected by Tagger The Tagger algorithm (http://www.broad.mit.edu/mpg/tagger) was used to select single- and multi-marker tests to capture all SNPs of minor allele frequency (MAF) ³5% with an r² ³0.8 in PRKAA2, PRKAB1 and PRKAB2 (see text for details). One SNP located >33 kb downstream from the end of PRKAB1 (rs278121) and two SNPs located >8 kb downstream from the end of PRKAB2 (rs2077749 and rs720609) were less well captured at r² =0.69 and 0.60, respectively. Supplementary Table 3: Association of variants in PRKAA2¸ PRKAB1 and PRKAB2 with quantitative traits Fasting plasma glucose (mmol/L) and the whole-body insulin sensitivity index (ISI) (47) were determined in 756 non-diabetic Scandinavian subjects (363 female). The latter was logarithmically transformed; values are mean ± SD (where SD = 0 indicates a single observation). These measures were compared by ANOVA depending on each of 22 single-marker and 18 multi-marker genotypic tests. The SNPs that define each multi-marker test (bottom panel for each gene) are numbered as in the top panel, and correspond to those in Table 2. M/M, homozygotes for the major allele; M/m, heterozygotes; m/m, homozygotes for the minor allele. 1 1, two copies of the multi-marker haplotype; 1 2, one copy of the multi-marker haplotype; 2 2, zero copies of the multi-marker haplotype. The only two nominally significant P values (*) are not reliable due to the low number of observations (N=2) in the outlier cells.