The association of GNB5 with Alzheimer disease revealed by genomic analysis restricted to variants impacting gene function.

Disease-associated variants identified from genome-wide association studies (GWASs) frequently map to non-coding areas of the genome such as introns and intergenic regions. An exclusive reliance on gene-agnostic methods of genomic investigation could limit the identification of relevant genes associated with polygenic diseases such as Alzheimer disease (AD). To overcome such potential restriction, we developed a gene-constrained analytical method that considers only moderate- and high-risk variants that affect gene coding sequences. We report here the application of this approach to publicly available datasets containing 181,388 individuals without and with AD and the resulting identification of 660 genes potentially linked to the higher AD prevalence among Africans/African Americans. By integration with transcriptome analysis of 23 brain regions from 2,728 AD case-control samples, we concentrated on nine genes that potentially enhance the risk of AD: AACS, GNB5, GNS, HIPK3, MED13, SHC2, SLC22A5, VPS35, and ZNF398. GNB5, the fifth member of the heterotrimeric G protein beta family encoding Gß5, is primarily expressed in neurons and is essential for normal neuronal development in mouse brain. Homozygous or compound heterozygous loss of function of GNB5 in humans has previously been associated with a syndrome of developmental delay, cognitive impairment, and cardiac arrhythmia. In validation experiments, we confirmed that Gnb5 heterozygosity enhanced the formation of both amyloid plaques and neurofibrillary tangles in the brains of AD model mice. These results suggest that gene-constrained analysis can complement the power of GWASs in the identification of AD-associated genes and may be more broadly applicable to other polygenic diseases.

Specific regulation of mechanical nociception by Gß5 involves GABA-B receptors.

Mechanical, thermal, and chemical pain sensation is conveyed by primary nociceptors, a subset of sensory afferent neurons. The intracellular regulation of the primary nociceptive signal is an area of active study. We report here the discovery of a Gß5-dependent regulatory pathway within mechanical nociceptors that restrains antinociceptive input from metabotropic GABA-B receptors. In mice with conditional knockout (cKO) of the gene that encodes Gß5 (Gnb5) targeted to peripheral sensory neurons, we demonstrate the impairment of mechanical, thermal, and chemical nociception. We further report the specific loss of mechanical nociception in Rgs7-Cre+/- Gnb5fl/fl mice but not in Rgs9-Cre+/- Gnb5fl/fl mice, suggesting that Gß5 might specifically regulate mechanical pain in regulator of G protein signaling 7-positive (Rgs7+) cells. Additionally, Gß5-dependent and Rgs7-associated mechanical nociception is dependent upon GABA-B receptor signaling since both were abolished by treatment with a GABA-B receptor antagonist and since cKO of Gß5 from sensory cells or from Rgs7+ cells potentiated the analgesic effects of GABA-B agonists. Following activation by the G protein-coupled receptor Mrgprd agonist ß-alanine, enhanced sensitivity to inhibition by baclofen was observed in primary cultures of Rgs7+ sensory neurons harvested from Rgs7-Cre+/- Gnb5fl/fl mice. Taken together, these results suggest that the targeted inhibition of Gß5 function in Rgs7+ sensory neurons might provide specific relief for mechanical allodynia, including that contributing to chronic neuropathic pain, without reliance on exogenous opioids.

Ancestry-specific high-risk gene variant profiling unmasks diabetes-associated genes.

How ancestry-associated genetic variance affects disparities in the risk for polygenic diseases and influences the identification of disease-associated genes warrant a deeper understanding. We hypothesized that the discovery of genes associated with polygenic diseases may be limited by overreliance on single-nucleotide polymorphism (SNP)-based genomic investigation, since most significant variants identified in genome-wide SNP association studies map to introns and intergenic regions of the genome. To overcome such potential limitation, we developed a gene-constrained and function-based analytical method centered on high-risk variants (hrV) that encode frameshifts, stopgains, or splice site disruption. We analyzed the total number of hrV per gene in populations of different ancestry, representing a total of 185 934 subjects. Using this analysis, we developed a quantitative index of hrV (hrVI) across 20 428 genes within each population. We then applied hrVI analysis to the discovery of genes associated with type 2 diabetes mellitus (T2DM), a polygenic disease with ancestry-related disparity. HrVI profiling and gene-to-gene comparisons of ancestry-specific hrV between the case (20 781 subjects) and control (24 440 subjects) populations in the T2DM national repository identified 57 genes associated with T2DM, 40 of which were discoverable only by ancestry-specific analysis. These results illustrate how function-based and ancestry-specific analysis of genetic variations can accelerate the identification of genes associated with polygenic diseases. Besides T2DM, such analysis may facilitate our understanding of the genetic basis for other polygenic diseases that are also greatly influenced by environmental and behavioral factors, such as obesity, hypertension, and Alzheimer's disease.