Table 1.
Risk of bias assessment using the Q-Genie tool.
| Study Reference (Study Design) |
1. Rationale for Study | 2. Selection and Definition of Outcome of Interest (Cases/Disease Status or a Quantitative Trait) | 3. Selection and Comparability of Comparison Groups (if Applicable) | 4. Technical Classification of the Exposure | 5. Non-Technical Classification of the Exposure | 6. Other Sources of Bias | 7. Sample Size and Power | 8. A priori Planning of Analyses | 9. Statistical Methods and Control for Confounding | 10. Testing of Assumptions and Inferences for Genetic Analyses | 11. Appropriateness of Inferences Drawn from Results | Total Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CASR | ||||||||||||
| Annerbo 2015 # [8] (Cross-sectional) |
4 | 4 | 0 | 4 | 2 | 1 | 1 | 4 | 2 | 4 | 7 | 33 |
| Arcidiacono 2009 # [10] (Case-control) |
4 | 4 | 4 | 4 | 2 | 1 | 1 | 4 | 2 | 2 | 7 | 35 |
| Bochud 2011 # [39] (Cross-sectional) |
6 | 6 | 0 | 4 | 2 | 1 | 1 | 4 | 6 | 3 | 7 | 40 |
| Cerani 2019 [9] (Mendalian randomisation study) |
6 | 6 | 4 | 4 | 2 | 4 | 4 | 5 | 6 | 5 | 7 | 53 |
| Chang 2015 [23] (Genome-wide association study) |
6 | 4 | 0 | 6 | 3 | 2 | 6 | 5 | 6 | 3 | 7 | 48 |
| Cole 1999 [40] (Cross-sectional) |
6 | 5 | 0 | 3 | 2 | 2 | 2 | 4 | 5 | 4 | 5 | 38 |
| Cole 2001 [41] (Cross-sectional) |
7 | 5 | 0 | 3 | 2 | 2 | 4 | 3 | 4 | 3 | 5 | 38 |
| Corebetta 2006 [42] (Case-control) |
6 | 6 | 6 | 5 | 2 | 2 | 2 | 4 | 5 | 2 | 5 | 45 |
| Guha 2015 [24] (Case-control) |
6 | 5 | 7 | 4 | 2 | 2 | 6 | 5 | 4 | 2 | 6 | 49 |
| Jorde 2013 [43] (Case-control) |
7 | 6 | 5 | 4 | 2 | 3 | 2 | 4 | 3 | 2 | 6 | 44 |
| Jung 2009 [25] (Population-and family-based association study) |
6 | 6 | 0 | 6 | 2 | 2 | 5 | 3 | 4 | 5 | 6 | 45 |
| Kapur 2010 [26] (Meta-analysis of genome-wide association study) |
7 | 4 | 4 | 2 | 3 | 3 | 7 | 6 | 6 | 5 | 6 | 53 |
| Laaksonen 2009 [27] (Cross-sectional) |
6 | 6 | 0 | 4 | 3 | 3 | 2 | 3 | 6 | 4 | 6 | 43 |
| Larsson 2017 [28] (Mendalian randomisation study) |
6 | 5 | 4 | 4 | 3 | 6 | 6 | 7 | 5 | 5 | 6 | 57 |
| Lorentzon 2001 [44] (Association study) |
6 | 4 | 0 | 2 | 2 | 2 | 4 | 4 | 4 | 2 | 5 | 35 |
| Majid 2015 [45] (Cross-sectional) |
7 | 5 | 0 | 4 | 2 | 3 | 2 | 4 | 3 | 4 | 6 | 40 |
| März 2007 [29] (Case-control) |
6 | 6 | 4 | 3 | 6 | 2 | 4 | 5 | 4 | 2 | 6 | 48 |
| O’Seaghdha 2010 [46] (Genome-wide association study) |
7 | 5 | 0 | 2 | 2 | 2 | 3 | 5 | 5 | 3 | 6 | 40 |
| Scillitani 2004 [11] (Cross-sectional) |
7 | 5 | 0 | 2 | 2 | 2 | 3 | 2 | 6 | 4 | 6 | 39 |
| Shakhssalim 2010 [48] (Case-control) |
6 | 4 | 4 | 2 | 2 | 2 | 2 | 3 | 3 | 4 | 4 | 36 |
| Siomou 2017 [52] (Case-control) |
4 | 4 | 3 | 2 | 2 | 5 | 2 | 2 | 2 | 2 | 4 | 32 |
| Vezzoli 2014 [30] (Cross-sectional) |
7 | 5 | 0 | 3 | 2 | 2 | 4 | 5 | 4 | 4 | 6 | 42 |
| Vezzoli 2011 [31] (Case-control) |
7 | 5 | 5 | 5 | 2 | 2 | 7 | 5 | 3 | 4 | 5 | 50 |
| Vezzoli 2002 [32] (Case-control) |
7 | 6 | 6 | 5 | 2 | 2 | 3 | 5 | 6 | 5 | 6 | 53 |
| Wang 2017 [19] (Case-control) |
7 | 5 | 5 | 2 | 2 | 5 | 7 | 6 | 7 | 4 | 6 | 56 |
| Wang 2007 # [53] (Cross-sectional) |
3 | 3 | 0 | 3 | 2 | 2 | 2 | 3 | 2 | 2 | 4 | 26 |
| VDR | ||||||||||||
| Ames 1999 [13] (Cross-sectional) |
7 | 5 | 0 | 4 | 2 | 2 | 2 | 4 | 5 | 3 | 6 | 40 |
| Ferrari 1999 [49] (Cross-sectional) |
4 | 5 | 0 | 3 | 2 | 4 | 3 | 4 | 5 | 2 | 4 | 36 |
| Jehan 2010 [54] (Association study) |
6 | 4 | 0 | 3 | 2 | 2 | 3 | 2 | 2 | 3 | 4 | 31 |
| Nakano 2000 [12] (Case-control) |
3 | 5 | 6 | 6 | 2 | 4 | 3 | 5 | 4 | 3 | 5 | 46 |
| Relan 2004 [55] (Case-control) |
4 | 4 | 4 | 3 | 2 | 2 | 3 | 3 | 1 | 2 | 5 | 33 |
| Different Gene Polymorphisms | ||||||||||||
| Arcidiacono 2018 [33] (Cross-sectional) |
7 | 5 | 0 | 4 | 2 | 5 | 4 | 6 | 6 | 6 | 7 | 52 |
| Bellia 2016 [50] (Cross-sectional) |
4 | 5 | 0 | 5 | 2 | 1 | 2 | 5 | 3 | 5 | 6 | 38 |
| Fujita 2013 [56] (Cross-sectional) |
4 | 2 | 0 | 2 | 1 | 1 | 2 | 2 | 2 | 3 | 4 | 23 |
| Gianfagna 2013 [34] (Cross-sectional) |
6 | 5 | 0 | 3 | 2 | 4 | 4 | 6 | 6 | 6 | 6 | 48 |
| Howles 2019 [35] (Genome-wide association study) |
7 | 4 | 0 | 6 | 2 | 3 | 4 | 5 | 5 | 6 | 7 | 49 |
| Hwang 2014 [36] (Case-control) |
7 | 4 | 4 | 5 | 4 | 4 | 2 | 6 | 7 | 4 | 7 | 54 |
| Kim 2018 [37] (Cross-sectional) |
7 | 4 | 0 | 7 | 4 | 6 | 7 | 6 | 7 | 6 | 7 | 61 |
| Koek 2010 [38] (Cross-sectional) |
7 | 5 | 0 | 6 | 4 | 3 | 5 | 6 | 6 | 6 | 7 | 55 |
| Masi 2007 [51] (Cross-sectional) |
7 | 6 | 0 | 4 | 2 | 1 | 1 | 6 | 2 | 3 | 7 | 39 |
| Shakhssalim 2014 [47] (Case-control) |
7 | 6 | 6 | 5 | 2 | 1 | 1 | 6 | 2 | 2 | 7 | 45 |
# only available as abstracts. Studies with control groups: poor quality ≤35 (red), >moderate quality 35 and ≤45 (yellow), good quality >45 (green); studies without control groups: poor quality ≤32 (red), moderate quality >32 and ≤40 (yellow), good quality >40 (green). Abbreviations: CASR: calcium-sensing receptor; VDR: vitamin D receptor.