{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T02:39:49Z","timestamp":1791427189709,"version":"4.3.3"},"reference-count":50,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"10","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2022,5,17]]},"abstract":"<jats:sec xml:lang=\"en\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p xml:lang=\"en\">\n                      The enterosalivary nitrate\u2013nitrite\u2013nitric oxide (NO\n                      <jats:sub>3<\/jats:sub>\n                      \u2013NO\n                      <jats:sub>2<\/jats:sub>\n                      \u2013NO) pathway generates NO following oral microbiota\u2010mediated production of salivary nitrite, potentially linking the oral microbiota to reduced cardiometabolic risk. Nitrite depletion by oral bacteria may also be important for determining the net nitrite available systemically. We examine if higher abundance of oral microbial genes favoring increased oral nitrite generation and decreased nitrite depletion is associated with a better cardiometabolic profile cross\u2010sectionally.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Methods and Results<\/jats:title>\n                    <jats:p xml:lang=\"en\">\n                      This study includes 764 adults (mean [SD] age 32 [9] years, 71% women) enrolled in ORIGINS (Oral Infections, Glucose Intolerance, and Insulin Resistance Study). Microbial DNA from subgingival dental plaques underwent 16S rRNA gene sequencing; PICRUSt2 was used to estimate functional gene profiles. To represent the different components and pathways of nitrogen metabolism in bacteria, predicted gene abundances were operationalized to create summary scores by (1) bacterial nitrogen metabolic pathway or (2) biochemical product (NO\n                      <jats:sub>2<\/jats:sub>\n                      , NO, or ammonia [NH\n                      <jats:sub>3<\/jats:sub>\n                      ]) formed by the action of the bacterial reductases encoded. Finally, nitrite generation\u2010to\u2010depletion ratios of gene abundances were created from the above summary scores. A composite cardiometabolic\n                      <jats:italic>Z<\/jats:italic>\n                      score was created from cardiometabolic risk variables, with higher scores associated with worse cardiometabolic health. We performed multivariable linear regression analysis with cardiometabolic\n                      <jats:italic>Z<\/jats:italic>\n                      score as the outcome and the gene abundance summary scores and ratios as predictor variables, adjusting for sex, age, race, and ethnicity in the simple adjusted model. A 1 SD higher NO versus NH\n                      <jats:sub>3<\/jats:sub>\n                      summary ratio was inversely associated with a \u22120.10 (false discovery rate\n                      <jats:italic>q<\/jats:italic>\n                      =0.003) lower composite cardiometabolic\n                      <jats:italic>Z<\/jats:italic>\n                      score in simple adjusted models. Higher NH\n                      <jats:sub>3<\/jats:sub>\n                      summary score (suggestive of nitrite depletion) was associated with higher cardiometabolic risk, with a 0.06 (false discovery rate\n                      <jats:italic>q<\/jats:italic>\n                      =0.04) higher composite cardiometabolic\n                      <jats:italic>Z<\/jats:italic>\n                      score.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p xml:lang=\"en\">Increased net capacity for nitrite generation versus depletion by oral bacteria, assessed through a metagenome estimation approach, is associated with lower levels of cardiometabolic risk.<\/jats:p>\n                  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