Post-transcriptional regulation and subcellular localization of G-protein γ7 subunit: implications for striatal function and behavioral responses to cocaine.

The striatal D1 dopamine receptor (D1R) and A2a adenosine receptor (A2aR) signaling pathways play important roles in drug-related behaviors. These receptors activate the Golf protein comprised of a specific combination of αolfß2γ7 subunits. During assembly, the γ7 subunit sets the cellular level of the Golf protein. In turn, the amount of Golf protein determines the collective output from both D1R and A2aR signaling pathways. This study shows the Gng7 gene encodes multiple γ7 transcripts differing only in their non-coding regions. In striatum, Transcript 1 is the predominant isoform. Preferentially expressed in the neuropil, Transcript 1 is localized in dendrites where it undergoes post-transcriptional regulation mediated by regulatory elements in its 3' untranslated region that contribute to translational suppression of the γ7 protein. Earlier studies on gene-targeted mice demonstrated loss of γ7 protein disrupts assembly of the Golf protein. In the current study, morphological analysis reveals the loss of the Golf protein is associated with altered dendritic morphology of medium spiny neurons. Finally, behavioral analysis of conditional knockout mice with cell-specific deletion of the γ7 protein in distinct populations of medium spiny neurons reveals differential roles of the Golf protein in mediating behavioral responses to cocaine. Altogether, these findings provide a better understanding of the regulation of γ7 protein expression, its impact on Golf function, and point to a new potential target and mechanisms for treating addiction and related disorders.

Temporal trends and geographic variations in mortality rates from tobacco and firearms in the United States.

We explored temporal trends and geographic variations in United States of America (US) mortality rates from smoking and firearms from 1999 to 2019. To do so, we used the publicly available Centers for Disease Control and Prevention (CDC) Wide Ranging Online Data for Epidemiologic Research (WONDER) with Multiple Cause of Death files from 1999 to 2019. Using age-specific rates and ArcGIS Pro Advanced software for Optimized Hot Spot Analyses from Esri, we generated maps of statistically significant spatial clusters with 90-99% confidence intervals with the Getis-Ord Gi* statistic for mortality from smoking-related causes and firearms. These data show temporal trends and geographic variations in mortality from smoking and firearms in the US. Smoking and firearm-related mortality from assault and suicide increased throughout the US and clustered in the Southeast. Firearm-related suicide also clustered in the continental West and Alaska. These descriptive data generate many hypotheses which are testable in analytic epidemiologic studies designed a priori to do so. The trends suggest smoking and firearm-related causes pose particular challenges to the Southeast and firearms also to the West and Alaska. These data may aid clinicians and public health authorities to implement evidence-based smoking avoidance and cessation programs as well as address firearm mortality, with particular attention to the areas of highest risks. As has been the case with cigarettes, individual behavior changes as well as societal changes are likely to be needed to achieve decreases in premature mortality.

Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study.

Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease. We selected 73 of these 704 participants with reliable confirmation of COVID-19 by PCR testing and high-quality physiological data for algorithm training to identify onset of COVID-19 using machine learning classification. The algorithm identified COVID-19 an average of 2.75 days before participants sought diagnostic testing with a sensitivity of 82% and specificity of 63%. The receiving operating characteristic (ROC) area under the curve (AUC) was 0.819 (95% CI [0.809, 0.830]). Including continuous temperature yielded an AUC 4.9% higher than without this feature. For further validation, we obtained SARS CoV-2 antibody in a subset of participants and identified 10 additional participants who self-reported COVID-19 disease with antibody confirmation. The algorithm had an overall ROC AUC of 0.819 (95% CI [0.809, 0.830]), with a sensitivity of 90% and specificity of 80% in these additional participants. Finally, we observed substantial variation in accuracy based on age and biological sex. Findings highlight the importance of including temperature assessment, using continuous physiological features for alignment, and including diverse populations in algorithm development to optimize accuracy in COVID-19 detection from wearables.

Genetics and prescription opioid use (GaPO): study design for consenting a cohort from an existing biobank to identify clinical and genetic factors influencing prescription opioid use and abuse.

BACKGROUND: Prescription opioids (POs) are commonly used to treat moderate to severe chronic pain in the health system setting. Although they improve quality of life for many patients, more work is needed to identify both the clinical and genetic factors that put certain individuals at high risk for developing opioid use disorder (OUD) following use of POs for pain relief. With a greater understanding of important risk factors, physicians will be better able to identify patients at highest risk for developing OUD for whom non-opioid alternative therapies and treatments should be considered. METHODS: We are conducting a prospective observational study that aims to identify the clinical and genetic factors most stongly associated with OUD. The study design leverages an existing biobank that includes whole exome sequencing and array genotyping. The biobank is maintained within an integrated health system, allowing for the large-scale capture and integration of genetic and non-genetic data. Participants are enrolled into the health system biobank via informed consent and then into a second study that focuses on opioid medication use. Data capture includes validated self-report surveys measuring addiction severity, depression, anxiety, and nicotine use, as well as additional clinical, prescription, and brain imaging data extracted from electronic health records. DISCUSSION: We will harness this multimodal data capture to establish meaningful patient phenotypes in order to understand the genetic and non-genetic contributions to OUD.

Selective Manipulation of G-Protein γ7 Subunit in Mice Provides New Insights into Striatal Control of Motor Behavior.

Stimulatory coupling of dopamine D1 (D1R) and adenosine A2A receptors (A2AR) to adenylyl cyclase within the striatum is mediated through a specific Gαolfß2γ7 heterotrimer to ultimately modulate motor behaviors. To dissect the individual roles of the Gαolfß2γ7 heterotrimer in different populations of medium spiny neurons (MSNs), we produced and characterized conditional mouse models, in which the Gng7 gene was deleted in either the D1R- or A2AR/D2R-expressing MSNs. We show that conditional loss of γ7 disrupts the cell type-specific assembly of the Gαolfß2γ7 heterotrimer, thereby identifying its circumscribed roles acting downstream of either the D1Rs or A2ARs in coordinating motor behaviors, including in vivo responses to psychostimulants. We reveal that Gαolfß2γ7/cAMP signal in D1R-MSNs does not impact spontaneous and amphetamine-induced locomotor behaviors in male and female mice, while its loss in A2AR/D2R-MSNs results in a hyperlocomotor phenotype and enhanced locomotor response to amphetamine. Additionally, Gαolfß2γ7/cAMP signal in either D1R- or A2AR/D2R-expressing MSNs is not required for the activation of PKA signaling by amphetamine. Finally, we show that Gαolfß2γ7 signaling acting downstream of D1Rs is selectively implicated in the acute locomotor-enhancing effects of morphine. Collectively, these results support the general notion that receptors use specific Gαßγ proteins to direct the fidelity of downstream signaling pathways and to elicit a diverse repertoire of cellular functions. Specifically, these findings highlight the critical role for the γ7 protein in determining the cellular level, and hence, the function of the Gαolfß2γ7 heterotrimer in several disease states associated with dysfunctional striatal signaling.SIGNIFICANCE STATEMENT Dysfunction or imbalance of cAMP signaling in the striatum has been linked to several neurologic and neuropsychiatric disorders, including Parkinson's disease, dystonia, schizophrenia, and drug addiction. By genetically targeting the γ7 subunit in distinct striatal neuronal subpopulations in mice, we demonstrate that the formation and function of the Gαolfß2γ7 heterotrimer, which represents the rate-limiting step for cAMP production in the striatum, is selectively disrupted. Furthermore, we reveal cell type-specific roles for Gαolfß2γ7-mediated cAMP production in the control of spontaneous locomotion as well as behavioral and molecular responses to psychostimulants. Our findings identify the γ7 protein as a novel therapeutic target for disease states associated with dysfunctional striatal cAMP signaling.

Genomic surveillance to combat COVID-19: challenges and opportunities.

Although the development and increasingly widespread availability of effective and safe vaccines provides the greatest hope for the future recovery from the increasingly devastating COVID-19 pandemic, there are other preventive efforts that offer an immediate route to decreasing morbidity and mortality. Genomic surveillance is emerging as a vital necessity to achieve effective mitigation and containment. Since SARS-CoV-2 variants have already been detected, it is crucial to obtain reliable evidence about whether they are more contagious, virulent, or more resistant to the available COVID-19 vaccines well before they spread throughout the world. Genomic surveillance leverages applications of next-generation sequencing, creates the availability of whole genome data, and advances phylogenetic methods. These methods offer novel means to detect variants that are phenotypically or antigenically different. Genomic surveillance will facilitate greater early anticipation as well as initiation of effective strategies to mitigate and contain outbreaks of SARS-CoV-2 variants and other novel viruses.

Different biases in meta-analyses of case-control and cohort studies: an example from genomics and precision medicine.

PURPOSE: Meta-analyses of observational studies reduce the role of chance but also introduce bias because the individual component studies are not randomized. Further, it is plausible that the bias may be different in case-control and cohort studies. We explored these issues in meta-analyses of observational studies of Opioid Use Disorder (OUD). METHODS: From a systematic literature review of 152 published meta-analyses, 11 fulfilled the initial inclusion criteria of observational studies of OUD. Of these, 9 were meta-analyses of case-control studies and 2 were meta-analyses of cohort studies but only 4 (3 case-control and 1 cohort) targeted more than one specific chromosomal location. RESULTS: The meta-analyses of the 3 case-control studies, which included 13 individual studies, identified 12 different single nucleotide polymorphisms on 6 different genes on 5 different chromosomes. None was the same as the gene on Chromosome 15 identified from the meta-analysis of the cohort studies. CONCLUSIONS: These data, from genetic studies, suggest biases are different in meta-analyses of case-control and cohort studies, perhaps due to greater selection bias in case-control studies. These observations have potential importance in the application of meta-analyses to many common and serious diseases, as well as genomics and precision medicine, including OUD.

A simplified SARS-CoV-2 detection protocol for research laboratories.

Widespread testing is required to limit the current public health crisis caused by the COVID-19 pandemic. Multiple tests protocols have been authorized by the food and drugs administration (FDA) under an emergency use authorization (EUA). The majority of these protocols are based on the gold-standard RT-qPCR test pioneered by the U.S. Centers for Disease Control and Prevention (CDC). However, there is still a widespread lack of testing in the US and many of the clinical diagnostics protocols require extensive human labor and materials that could face supply shortages and present biosafety concerns. Given the need to develop alternative reagents and approaches to provide nucleic-acid testing in the face of heightened demand and potential shortages, we have developed a simplified SARS-CoV-2 testing protocol adapted for its use in research laboratories with minimal molecular biology equipment and expertise. The protocol utilizes TRIzol to purify the viral RNA from different types of clinical specimens, requires minimal BSL-1 precautions and, given its high sensitivity, can be easily adapted to pooling samples strategies.

Assessment of Probable Opioid Use Disorder Using Electronic Health Record Documentation.

Importance: Electronic health records are a potentially valuable source of information for identifying patients with opioid use disorder (OUD). Objective: To evaluate whether proxy measures from electronic health record data can be used reliably to identify patients with probable OUD based on Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) criteria. Design, Setting, and Participants: This retrospective cross-sectional study analyzed individuals within the Geisinger health system who were prescribed opioids between December 31, 2000, and May 31, 2017, using a mixed-methods approach. The cohort was identified from 16 253 patients enrolled in a contract-based, Geisinger-specific medication monitoring program (GMMP) for opioid use, including patients who maintained or violated contract terms, as well as a demographically matched control group of 16 253 patients who were prescribed opioids but not enrolled in the GMMP. Substance use diagnoses and psychiatric comorbidities were assessed using automated electronic health record summaries. A manual medical record review procedure using DSM-5 criteria for OUD was completed for a subset of patients. The analysis was conducted beginning from June 5, 2017, until May 29, 2020. Main Outcomes and Measures: The primary outcome was the prevalence of OUD as defined by proxy measures for DSM-5 criteria for OUD as well as the prevalence of comorbidities among patients prescribed opioids within an integrated health system. Results: Among the 16 253 patients enrolled in the GMMP (9309 women [57%]; mean [SD] age, 52 [14] years), OUD diagnoses as defined by diagnostic codes were present at a much lower rate than expected (291 [2%]), indicating the necessity for alternative diagnostic strategies. The DSM-5 criteria for OUD can be assessed using manual medical record review; a manual review of 200 patients in the GMMP and 200 control patients identifed a larger percentage of patients with probable moderate to severe OUD (GMMP, 145 of 200 [73%]; and control, 27 of 200 [14%]) compared with the prevalence of OUD assessed using diagnostic codes. Conclusions and Relevance: These results suggest that patients with OUD may be identified using information available in the electronic health record, even when diagnostic codes do not reflect this diagnosis. Furthermore, the study demonstrates the utility of coding for DSM-5 criteria from medical records to generate a quantitative DSM-5 score that is associated with OUD severity.

Characterization of genetic and phenotypic heterogeneity of obstructive sleep apnea using electronic health records.

BACKGROUND: Obstructive sleep apnea (OSA) is defined by frequent episodes of reduced or complete cessation of airflow during sleep and is linked to negative health outcomes. Understanding the genetic factors influencing expression of OSA may lead to new treatment strategies. Electronic health records (EHRs) can be leveraged to both validate previously reported OSA-associated genomic variation and detect novel relationships between these variants and comorbidities. METHODS: We identified candidate single nucleotide polymorphisms (SNPs) via systematic literature review of existing research. Using datasets available at Geisinger (n = 39,407) and Vanderbilt University Medical Center (n = 24,084), we evaluated associations between 40 previously implicated SNPs and OSA diagnosis, defined using clinical codes. We also evaluated associations between these SNPs and OSA severity measures obtained from sleep reports at Geisinger (n = 6571). Finally, we used a phenome-wide association study approach to help reveal pleiotropic genetic effects between OSA candidate SNPs and other clinical codes and laboratory values available in the EHR. RESULTS: Most previously reported OSA candidate SNPs showed minimal to no evidence for associations with OSA diagnosis or severity in the EHR-derived datasets. Three SNPs in LEPR, MMP-9, and GABBR1 validated for an association with OSA diagnosis in European Americans; the SNP in GABBR1 was associated following meta-analysis of results from both clinical populations. The GABBR1 and LEPR SNPs, and one additional SNP, were associated with OSA severity measures in European Americans from Geisinger. Three additional candidate OSA SNPs were not associated with OSA-related traits but instead with hyperlipidemia and autoimmune diseases of the thyroid. CONCLUSIONS: To our knowledge, this is one of the largest candidate gene studies and one of the first phenome-wide association studies of OSA genomic variation. Results validate genetic associates with OSA in the LEPR, MMP-9 and GABBR1 genes, but suggest that the majority of previously identified genetic associations with OSA may be false positives. Phenome-wide analyses provide evidence of mediated pleiotropy. Future well-powered genome-wide association analyses of OSA risk and severity across populations with diverse ancestral backgrounds are needed. The comprehensive nature of the analyses represents a platform for informing future work focused on understanding how genetic data can be useful to informing treatment of OSA and related comorbidities.

Temporal Trends and Geographic Variations in Mortality Rates from Prescription Opioids: Lessons from Florida and West Virginia.

OBJECTIVES: To explore temporal trends and geographic variations in mortality from prescription opioids from 1999 to 2016. METHODS: Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research Multiple Cause of Death files were used to calculate age-adjusted rates and 95% confidence intervals (CIs) and create spatial cluster maps. RESULTS: From 1999 to 2016, counties in West Virginia experienced the highest overall mortality rates in the United States from prescription opioids. Specifically, from 1999 to 2004, the highest rate in West Virginia of 24.87/100,000 (95% CI 17.84-33.73) was the fourth highest in the United States. From 2005 to 2009, West Virginia experienced the highest rate in the United States, 60.72/100,000 (95% CI 47.33-76.71). From 2010 to 2016, West Virginia also experienced the highest rate in the United States, which was 90.24/100,000 (95% CI 73.11-107.36). As such, overall, West Virginia experienced the highest rates in the United States and the largest increases overall of ~3.6-fold between 1999 and 2004 and 2010 and 2016. From 1999 to 2004, Florida had no "hot spots," but from 2006 to 2010 they did appear, and from 2011 to 2016, they disappeared. CONCLUSIONS: These data show markedly divergent temporal trends and geographic variations in mortality rates from prescription opioids, especially in the southern United States. Specifically, although initial rates were high and continued to increase alarmingly in West Virginia, they increased but then decreased in Florida. These descriptive data generate hypotheses requiring testing in analytic epidemiological studies. Understanding the divergent patterns of prescription opioid-related deaths, especially in West Virginia and Florida, may have important clinical and policy implications.

Multisite validation of a simple electronic health record algorithm for identifying diagnosed obstructive sleep apnea.

STUDY OBJECTIVES: We examined the performance of a simple algorithm to accurately distinguish cases of diagnosed obstructive sleep apnea (OSA) and noncases using the electronic health record (EHR) across six health systems in the United States. METHODS: Retrospective analysis of EHR data was performed. The algorithm defined cases as individuals with ≥ 2 instances of specific International Classification of Diseases (ICD)-9 and/or ICD-10 diagnostic codes (327.20, 327.23, 327.29, 780.51, 780.53, 780.57, G4730, G4733 and G4739) related to sleep apnea on separate dates in their EHR. Noncases were defined by the absence of these codes. Using chart reviews on 120 cases and 100 noncases at each site (n = 1,320 total), positive predictive value (PPV) and negative predictive value (NPV) were calculated. RESULTS: The algorithm showed excellent performance across sites, with a PPV (95% confidence interval) of 97.1 (95.6, 98.2) and NPV of 95.5 (93.5, 97.0). Similar performance was seen at each site, with all NPV and PPV estimates ≥ 90% apart from a somewhat lower PPV of 87.5 (80.2, 92.8) at one site. A modified algorithm of ≥ 3 instances improved PPV to 94.9 (88.5, 98.3) at this site, but excluded an additional 18.3% of cases. Thus, performance may be further improved by requiring additional codes, but this reduces the number of determinate cases. CONCLUSIONS: A simple EHR-based case-identification algorithm for diagnosed OSA showed excellent predictive characteristics in a multisite sample from the United States. Future analyses should be performed to understand the effect of undiagnosed disease in EHR-defined noncases. This algorithm has wide-ranging applications for EHR-based OSA research.

Establishing and Maintaining Research Integrity at Academic Institutions: Challenges and Opportunities.

Integrity and trust are essential attributes of medical researchers. Research misconduct represents clear and present dangers to academic institutions and their faculty, residents, students, and staff. To achieve and maintain public trust, medical researchers must achieve and maintain research integrity. To do so requires synchronicity and collaboration between and within academic institutions. Substantial failures to maintain research integrity by institutional leadership will lead to increasing demands to do so from the funding organizations and the general public. This, in turn, will lead to avoidable consequences of substantial penalties, financial and otherwise, adverse publicity, and reputational damage. Researchers must self-regulate to avoid pitfalls, including those created by changes in the medical care delivery system that have decreased the influence of health care providers and increased the influence of outside legal and business interests. Our common goal should be to return public trust in our research enterprise that has done so much good for so many, but requires the establishment and maintenance of vigilance to establish and maintain research integrity.

Rare-variant pathogenicity triage and inclusion of synonymous variants improves analysis of disease associations of orphan G protein-coupled receptors.

The pace of deorphanization of G protein-coupled receptors (GPCRs) has slowed, and new approaches are required. Small molecule targeting of orphan GPCRs can potentially be of clinical benefit even if the endogenous receptor ligand has not been identified. Many GPCRs lack common variants that lead to reproducible genome-wide disease associations, and rare-variant approaches have emerged as a viable alternative to identify disease associations for such genes. Therefore, our goal was to prioritize orphan GPCRs by determining their associations with human diseases in a large clinical population. We used sequence kernel association tests to assess the disease associations of 85 orphan or understudied GPCRs in an unselected cohort of 51,289 individuals. Using rare loss-of-function variants, missense variants predicted to be pathogenic or likely pathogenic, and a subset of rare synonymous variants that cause large changes in local codon bias as independent data sets, we found strong, phenome-wide disease associations shared by two or more variant categories for 39% of the GPCRs. To validate the bioinformatics and sequence kernel association test analyses, we functionally characterized rare missense and synonymous variants of GPR39, a family A GPCR, revealing altered expression or Zn2+-mediated signaling for members of both variant classes. These results support the utility of rare variant analyses for identifying disease associations for GPCRs that lack impactful common variants. We highlight the importance of rare synonymous variants in human physiology and argue for their routine inclusion in any comprehensive analysis of genomic variants as potential causes of disease.

TM6SF2 rs58542926 impacts lipid processing in liver and small intestine.

The transmembrane 6 superfamily member 2 (TM6SF2) loss-of-function variant rs58542926 is a genetic risk factor for nonalcoholic fatty liver disease and progression to fibrosis but is paradoxically associated with lower levels of hepatically derived triglyceride-rich lipoproteins. TM6SF2 is expressed predominantly in liver and small intestine, sites for triglyceride-rich lipoprotein biogenesis and export. In light of this, we hypothesized that TM6SF2 may exhibit analogous effects on both liver and intestine lipid homeostasis. To test this, we genotyped rs58542926 in 983 bariatric surgery patients from the Geisinger Medical Center for Nutrition and Weight Management, Geisinger Health System, in Pennsylvania and from 3,556 study participants enrolled in the Amish Complex Disease Research Program. Although these two cohorts have different metabolic profiles, carriers in both cohorts had improved fasting lipid profiles. Importantly, following a high-fat challenge, carriers in the Amish Complex Disease Research Program cohort exhibited significantly lower postprandial serum triglycerides, suggestive of a role for TM6SF2 in the small intestine. To gain further insight into this putative role, effects of TM6SF2 deficiency were studied in a zebrafish model and in cultured human Caco-2 enterocytes. In both systems TM6SF2 deficiency resulted in defects in small intestine metabolism in response to dietary lipids, including significantly increased lipid accumulation, decreased lipid clearance, and increased endoplasmic reticulum stress. CONCLUSIONS: These data strongly support a role of TM6SF2 in the regulation of postprandial lipemia, potentially through a similar function for TM6SF2 in the lipidation and/or export of both hepatically and intestinally derived triglyceride-rich lipoproteins. (Hepatology 2017;65:1526-1542).

Disruption of G-protein γ5 subtype causes embryonic lethality in mice.

Heterotrimeric G-proteins modulate many processes essential for embryonic development including cellular proliferation, migration, differentiation, and survival. Although most research has focused on identifying the roles of the various αsubtypes, there is growing recognition that similarly divergent ßγ dimers also regulate these processes. In this paper, we show that targeted disruption of the mouse Gng5 gene encoding the γ5 subtype produces embryonic lethality associated with severe head and heart defects. Collectively, these results add to a growing body of data that identify critical roles for the γ subunits in directing the assembly of functionally distinct G-αßγ trimers that are responsible for regulating diverse biological processes. Specifically, the finding that loss of the G-γ5 subtype is associated with a reduced number of cardiac precursor cells not only provides a causal basis for the mouse phenotype but also raises the possibility that G-ßγ5 dependent signaling contributes to the pathogenesis of human congenital heart problems.

Preferential assembly of G-αßγ complexes directed by the γ subunits.

Assembly of the G-αßγ heterotrimer is required for receptor signaling. Although much has been learned about the assembly process itself, the identities of the G-αßγ combinations that actually exist in physiological setting are largely unknown. Moreover, there is uncertainty regarding whether the individual subunits associate by a random process, or combine by a regulated process to form quasi-stable G-αßγ complexes. In this chapter, we will focus on emerging genetic -evidence that supports the latter model. Specifically, we will discuss how use of gene targeted mice has revealed preferential assembly of the striatal-specific Gα(olf)ß(2)γ(7) complex occurs by a sequential process that is directed by the γ(7) subunit. The existence of specific G-αßγ complexes responsible for transducing the signals from different receptors may have profound implications by providing a possible explanation for biased agonism.

Synergistic roles for G-protein γ3 and γ7 subtypes in seizure susceptibility as revealed in double knock-out mice.

The functions of different G-protein αßγ subunit combinations are traditionally ascribed to their various α components. However, the discovery of similarly diverse γ subtypes raises the possibility that they may also contribute to specificity. To test this possibility, we used a gene targeting approach to determine whether the closely related γ(3) and γ(7) subunits can perform functionally interchangeable roles in mice. In contrast to single knock-out mice that show normal survival, Gng3(-/-)Gng7(-/-) double knock-out mice display a progressive seizure disorder that dramatically reduces their median life span to only 75 days. Biochemical analyses reveal that the severe phenotype is not due to redundant roles for the two γ subunits in the same signaling pathway but rather is attributed to their unique actions in different signaling pathways. The results suggest that the γ(3) subunit is a component of a G(i/o) protein that is required for γ-aminobutyric acid, type B, receptor-regulated neuronal excitability, whereas the γ(7) subunit is a component of a G(olf) protein that is responsible for A(2A) adenosine or D(1) dopamine receptor-induced neuro-protective response. The development of this mouse model offers a novel experimental framework for exploring how signaling pathways integrate to produce normal brain function and how their combined dysfunction leads to spontaneous seizures and premature death. The results underscore the critical role of the γ subunit in this process.

Adenosine A2A receptor signaling and golf assembly show a specific requirement for the gamma7 subtype in the striatum.

The adenosine A(2A) receptor (A(2A)R) is increasingly recognized as a novel therapeutic target in Parkinson disease. In striatopallidal neurons, the G-protein α(olf) subtype is required to couple this receptor to adenylyl cyclase activation. It is now well established that the ßγ dimer also performs an active role in this signal transduction process. In principal, sixty distinct ßγ dimers could arise from combinatorial association of the five known ß and 12 γ subunit genes. However, key questions regarding which ßγ subunit combinations exist and whether they perform specific signaling roles in the context of the organism remain to be answered. To explore these questions, we used a gene targeting approach to specifically ablate the G-protein γ(7) subtype. Revealing a potentially new signaling paradigm, we show that the level of the γ(7) protein controls the hierarchial assembly of a specific G-protein α(olf)ß(2)γ(7) heterotrimer in the striatum. Providing a probable basis for the selectivity of receptor signaling, we further demonstrate that loss of this specific G-protein heterotrimer leads to reduced A(2A)R activation of adenylyl cyclase. Finally, substantiating an important role for this signaling pathway in pyschostimulant responsiveness, we show that mice lacking the G-protein γ(7) subtype exhibit an attenuated behavioral response to caffeine. Collectively, these results further support the A(2A)R G-protein α(olf)ß(2)γ(7) interface as a possible therapeutic target for Parkinson disease.