Timing of Parathyroidectomy Does Not Influence Renal Function After Kidney Transplantation

BACKGROUND: Parathyroidectomy (PTx) is the treatment of choice for end-stage renal disease (ESRD) patients with therapy-resistant hyperparathyroidism (HPT). The optimal timing of PTx for ESRD-related HPT-before or after kidney transplantation (KTx)-is subject of debate.METHODS: Patients with ESRD-related HPT who underwent both PTx and KTx between 1994 and 2015 were included in a multicenter retrospective study in four university hospitals. Two groups were formed according to treatment sequence: PTx before KTx (PTxKTx) and PTx after KTx (KTxPTx). Primary endpoint was renal function (eGFR, CKD-EPI) between both groups at several time points post-transplantation. Correlation between the timing of PTx and KTx and the course of eGFR was assessed using generalized estimating equations (GEE).RESULTS: The PTxKTx group consisted of 102 (55.1%) and the KTxPTx group of 83 (44.9%) patients. Recipient age, donor type, PTx type, and pre-KTx PTH levels were significantly different between groups. At 5 years after transplantation, eGFR was similar in the PTxKTx group (eGFR 44.5 ± 4.0 ml/min/1.73 m2) and KTxPTx group (40.0 ± 6.4 ml/min/1.73 m2, p = 0.43). The unadjusted GEE model showed that timing of PTx was not correlated with graft function over time (mean difference -1.0 ml/min/1.73 m2, 95% confidence interval -8.4 to 6.4, p = 0.79). Adjustment for potential confounders including recipient age and sex, various donor characteristics, PTx type, and PTH levels did not materially influence the results.CONCLUSIONS: In this multicenter cohort study, timing of PTx before or after KTx does not independently impact graft function over time.</p

Timing of Parathyroidectomy Does Not Influence Renal Function After Kidney Transplantation

BACKGROUND: Parathyroidectomy (PTx) is the treatment of choice for end-stage renal disease (ESRD) patients with therapy-resistant hyperparathyroidism (HPT). The optimal timing of PTx for ESRD-related HPT-before or after kidney transplantation (KTx)-is subject of debate. METHODS: Patients with ESRD-related HPT who underwent both PTx and KTx between 1994 and 2015 were included in a multicenter retrospective study in four university hospitals. Two groups were formed according to treatment sequence: PTx before KTx (PTxKTx) and PTx after KTx (KTxPTx). Primary endpoint was renal function (eGFR, CKD-EPI) between both groups at several time points post-transplantation. Correlation between the timing of PTx and KTx and the course of eGFR was assessed using generalized estimating equations (GEE). RESULTS: The PTxKTx group consisted of 102 (55.1%) and the KTxPTx group of 83 (44.9%) patients. Recipient age, donor type, PTx type, and pre-KTx PTH levels were significantly different between groups. At 5 years after transplantation, eGFR was similar in the PTxKTx group (eGFR 44.5 ± 4.0 ml/min/1.73 m2) and KTxPTx group (40.0 ± 6.4 ml/min/1.73 m2, p = 0.43). The unadjusted GEE model showed that timing of PTx was not correlated with graft function over time (mean difference -1.0 ml/min/1.73 m2, 95% confidence interval -8.4 to 6.4, p = 0.79). Adjustment for potential confounders including recipient age and sex, various donor characteristics, PTx type, and PTH levels did not materially influence the results. CONCLUSIONS: In this multicenter cohort study, timing of PTx before or after KTx does not independently impact graft function over time

Molecular Genetic Screening in Patients With ACE Inhibitor/Angiotensin Receptor Blocker-Induced Angioedema to Explore the Role of Hereditary Angioedema Genes

Angioedema is a relatively rare but potentially life-threatening adverse reaction to angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARBs). As with hereditary forms of angioedema (HAE), this adverse reaction is mediated by bradykinin. Research suggests that ACEi/ARB-induced angioedema has a multifactorial etiology. In addition, recent case reports suggest that some ACEi/ARB-induced angioedema patients may carry pathogenic HAE variants. The aim of the present study was to investigate the possible association between ACEi/ARB-induced angioedema and HAE genes via systematic molecular genetic screening in a large cohort of ACEi/ARB-induced angioedema cases. Targeted re-sequencing of five HAE-associated genes (SERPING1, F12, PLG, ANGPT1, and KNG1) was performed in 212 ACEi/ARB-induced angioedema patients recruited in Germany/Austria, Sweden, and Denmark, and in 352 controls from a German cohort. Among patients, none of the identified variants represented a known pathogenic variant for HAE. Moreover, no significant association with ACEi/ARB-induced angioedema was found for any of the identified common [minor allele frequency (MAF) &gt;5%] or rare (MAF &lt; 5%) variants. However, several non-significant trends suggestive of possible protective effects were observed. The lowest p-value for an individual variant was found in PLG (rs4252129, p.R523W, p = 0.057, p.adjust &gt; 0.999, Fisher’s exact test). Variant p.R523W was found exclusively in controls and has previously been associated with decreased levels of plasminogen, a precursor of plasmin which is part of a pathway directly involved in bradykinin production. In addition, rare, potentially functional variants (MAF &lt; 5%, Phred-scaled combined annotation dependent depletion score &gt;10) showed a nominally significant enrichment in controls both: 1) across all five genes; and 2) in the F12 gene alone. However, these results did not withstand correction for multiple testing. In conclusion, our results suggest that HAE-associated mutations are, at best, a rare cause of ACEi/ARB-induced angioedema. Furthermore, we were unable to identify a significant association between ACEi/ARB-induced angioedema and other variants in the investigated genes. Further studies with larger sample sizes are warranted to draw more definite conclusions concerning variants with limited effect sizes, including protective variants

Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li + PGS ) in patients with BD. To gain further insights into lithium’s possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li + PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi + Gen: N = 2367) and replicated in the combined PsyCourse ( N = 89) and BipoLife ( N = 102) studies. The associations of Li + PGS and lithium treatment response — defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P &lt; 0.05. Li + PGS was positively associated with lithium treatment response in the ConLi + Gen cohort, in both the categorical ( P = 9.8 × 10 − 12 , R 2 = 1.9%) and continuous ( P = 6.4 × 10 − 9 , R 2 = 2.6%) outcomes. Compared to bipolar patients in the 1 st decile of the risk distribution, individuals in the 10 th decile had 3.47-fold (95%CI: 2.22–5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome ( P = 3.9 × 10 − 4 , R 2 = 0.9%), but not for the continuous outcome ( P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li + PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment

Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health&nbsp;disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithiums possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P &lt; 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 10-12, R2 = 1.9%) and continuous (P = 6.4 × 10-9, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10-4, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment

Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder

International audienceLithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li + PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li + PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi + Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li + PGS and lithium treatment responsedefined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li + PGS was positively associated with lithium treatment response in the ConLi + Gen cohort, in both the categorical (P = 9.8 × 10 −12 , R 2 = 1.9%) and continuous (P = 6.4 × 10 −9 , R 2 = 2.6%) outcomes. Compared to bipolar patients in the 1 st decile of the risk distribution, individuals in the 10 th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10 −4 , R 2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li + PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment