{"doi":"10.1210/clinem/dgaa741","title":"Genotype-Phenotype Features of Germline Variants of the <i>TMEM127</i> Pheochromocytoma Susceptibility Gene: A 10-Year Update","abstract":"PURPOSE: This work aimed to evaluate genotype-phenotype associations in individuals carrying germline variants of transmembrane protein 127 gene (TMEM127), a poorly known gene that confers susceptibility to pheochromocytoma (PHEO) and paraganglioma (PGL). DESIGN: Data were collected from a registry of probands with TMEM127 variants, published reports, and public databases. MAIN OUTCOME ANALYSIS: Clinical, genetic, and functional associations were determined. RESULTS: The cohort comprised 110 index patients (111 variants) with a mean age of 45 years (range, 21-84 years). Females were predominant (76 vs 34, P < .001). Most patients had PHEO (n = 94; 85.5%), although PGL (n = 10; 9%) and renal cell carcinoma (RCC, n = 6; 5.4%) were also detected, either alone or in combination with PHEO. One-third of the cases had multiple tumors, and known family history was reported in 15.4%. Metastatic PHEO/PGL was rare (2.8%). Epinephrine alone, or combined with norepinephrine, accounted for 82% of the catecholamine profiles of PHEO/PGLs. Most variants (n = 63) occurred only once and 13 were recurrent (2-12 times). Although nontruncating variants were less frequent than truncating changes overall, they were predominant in non-PHEO clinical presentations (36% PHEO-only vs 69% other, P < .001) and clustered disproportionately within transmembrane regions (P < .01), underscoring the relevance of these domains for TMEM127 function. Integration of clinical and previous experimental data supported classification of variants into 4 groups based on mutation type, localization, and predicted disruption. CONCLUSIONS: Patients with TMEM127 variants often resemble sporadic nonmetastatic PHEOs. PGL and RCC may also co-occur, although their causal link requires further evaluation. We propose a new classification to predict variant pathogenicity and assist with carrier surveillance.","journal":"The Journal of Clinical Endocrinology & Metabolism","year":2020,"id":105766,"datarank":0.7942011483990067,"base_score":3.1780538303479458,"endowment":3.1780538303479458,"self_citation_contribution":0.47670807455219194,"citation_network_contribution":0.31749307384681474,"self_endowment_contribution":0.47670807455219194,"citer_contribution":0.31749307384681474,"corpus_percentile":74.68863618782393,"corpus_rank":3273,"citation_count":23,"citer_count":15,"citers_with_citation_signal":10,"citers_with_endowment":10,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.758,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":400949,"name":"Shahida K. 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